diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index f42c5c7..33734cb 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -69,7 +69,7 @@ jobs:
         with:
           github_token: ${{ secrets.GITHUB_TOKEN }}
           publish_dir: ./book/_book
-          destination_dir: dev
+          destination_dir: latest
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
diff --git a/notebooks/part1/01_naive.ipynb b/notebooks/part1/01_naive.ipynb
index 9e87f50..d6c5cdc 100644
--- a/notebooks/part1/01_naive.ipynb
+++ b/notebooks/part1/01_naive.ipynb
@@ -27,7 +27,72 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 1,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>points</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2021-01-01</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2021-01-02</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2021-01-03</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2021-01-04</th>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2021-01-05</th>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            points\n",
+              "2021-01-01       0\n",
+              "2021-01-02       0\n",
+              "2021-01-03       0\n",
+              "2021-01-04       1\n",
+              "2021-01-05       1"
+            ]
+          },
+          "execution_count": 1,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from tsbook.datasets.simple import SimpleDataset\n",
         "\n",
@@ -36,9 +101,7 @@
         "y = dataset.load(\"y\")\n",
         "\n",
         "y.head()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -51,13 +114,13 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 2,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from sktime.forecasting.model_selection import temporal_train_test_split\n",
         "y_train, y_test = temporal_train_test_split(y, test_size=36)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -68,14 +131,35 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 3,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='points'>)"
+            ]
+          },
+          "execution_count": 3,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from sktime.utils.plotting import plot_series\n",
         "\n",
         "plot_series(y, labels=[\"Observações\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -95,15 +179,347 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 4,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-205d7c90-e5ff-403d-8f67-7be1af3a7918 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-205d7c90-e5ff-403d-8f67-7be1af3a7918' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>NaiveForecaster()</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('b3cfce59-09b5-4152-9c6d-3f4ed0df14e9') type=\"checkbox\" checked><label for=UUID('b3cfce59-09b5-4152-9c6d-3f4ed0df14e9') class='sk-toggleable__label sk-toggleable__label-arrow'>NaiveForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.naive.NaiveForecaster.html\">?<span>Documentation for NaiveForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>NaiveForecaster()</pre></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "NaiveForecaster()"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.forecasting.naive import NaiveForecaster\n",
         "\n",
         "model = NaiveForecaster(strategy=\"last\")\n",
         "model"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -114,12 +530,344 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 5,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-0164c948-1dd7-477b-bebe-21440808e13f {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-0164c948-1dd7-477b-bebe-21440808e13f a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-0164c948-1dd7-477b-bebe-21440808e13f' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>NaiveForecaster()</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('be73e165-6a27-45c3-b34d-516179c07f9e') type=\"checkbox\" checked><label for=UUID('be73e165-6a27-45c3-b34d-516179c07f9e') class='sk-toggleable__label sk-toggleable__label-arrow'>NaiveForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.naive.NaiveForecaster.html\">?<span>Documentation for NaiveForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>NaiveForecaster()</pre></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "NaiveForecaster()"
+            ]
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "model.fit(y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -130,12 +878,70 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 6,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>points</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2021-03-06</th>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2021-03-07</th>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2021-03-08</th>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2021-03-09</th>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            points\n",
+              "2021-03-06     1.0\n",
+              "2021-03-07     1.0\n",
+              "2021-03-08     1.0\n",
+              "2021-03-09     1.0"
+            ]
+          },
+          "execution_count": 6,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "model.predict(fh=[1,2,3,4])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -146,14 +952,35 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 7,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='points'>)"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_pred = model.predict(fh=y_test.index)\n",
         "\n",
         "plot_series(y_train, y_test, y_pred, labels=[\"Treino\", \"Teste\", \"Previsão\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -166,7 +993,30 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 8,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='points'>)"
+            ]
+          },
+          "execution_count": 8,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "model.set_params(\n",
         "    strategy=\"mean\",\n",
@@ -178,9 +1028,7 @@
         "\n",
         "\n",
         "plot_series(y_train, y_test, y_pred, labels=[\"Treino\", \"Teste\", \"Previsão\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -191,7 +1039,30 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 9,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='points'>)"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "model.set_params(\n",
         "    sp=6,\n",
@@ -201,9 +1072,7 @@
         "model.fit(y_train)\n",
         "y_pred = model.predict(fh=y_test.index)\n",
         "plot_series(y_train, y_test, y_pred, labels=[\"Treino\", \"Teste\", \"Previsão\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -215,12 +1084,23 @@
   ],
   "metadata": {
     "kernelspec": {
-      "name": "python3",
+      "display_name": "tsbook-py3.11",
       "language": "python",
-      "display_name": "Python 3 (ipykernel)",
-      "path": "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/share/jupyter/kernels/python3"
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.11"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 4
-}
\ No newline at end of file
+}
diff --git a/notebooks/part1/02_components_and_diff.ipynb b/notebooks/part1/02_components_and_diff.ipynb
index f0fcd66..7c891c2 100644
--- a/notebooks/part1/02_components_and_diff.ipynb
+++ b/notebooks/part1/02_components_and_diff.ipynb
@@ -22,7 +22,30 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 1,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 1,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from tsbook.datasets.retail import SyntheticRetail\n",
         "from sktime.utils.plotting import plot_series\n",
@@ -31,9 +54,7 @@
         "y_train, y_test = dataset.load(\"y_train\", \"y_test\")\n",
         "\n",
         "plot_series(y_train, y_test, labels=[\"Treino\", \"Teste\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -63,16 +84,35 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 2,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/var/folders/_2/9y4tsvdd2n3gqjgd2zmlr1km0000gn/T/ipykernel_35862/2914460266.py:5: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
+            "  fig.show()\n"
+          ]
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1200x800 with 3 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from sktime.utils.plotting import plot_correlations\n",
         "\n",
         "\n",
         "fig, ax = plot_correlations(y_train, lags=60)\n",
         "fig.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -147,24 +187,377 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 3,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-4da75756-dde0-4b0e-b181-ca778cf64aec {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-4da75756-dde0-4b0e-b181-ca778cf64aec a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-4da75756-dde0-4b0e-b181-ca778cf64aec' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogTransformer()</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('7b517ecd-e12e-47dc-b399-641f8b234310') type=\"checkbox\" checked><label for=UUID('7b517ecd-e12e-47dc-b399-641f8b234310') class='sk-toggleable__label sk-toggleable__label-arrow'>LogTransformer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.boxcox.LogTransformer.html\">?<span>Documentation for LogTransformer</span></a></label><div class=\"sk-toggleable__content\"><pre>LogTransformer()</pre></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "LogTransformer()"
+            ]
+          },
+          "execution_count": 3,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.transformations.series.boxcox import LogTransformer\n",
         "log_transformer = LogTransformer()\n",
         "log_transformer.fit(y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 4,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_train_log = log_transformer.transform(y_train)\n",
         "plot_series(y_train_log, labels=[\"Logaritmo\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -183,7 +576,30 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 5,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from sktime.transformations.series.detrend import Detrender, Deseasonalizer\n",
         "\n",
@@ -192,9 +608,7 @@
         "detrender.fit(y_train)\n",
         "y_train_detrended = detrender.transform(y_train)\n",
         "plot_series(y_train_detrended, labels=[\"Detrended\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -205,13 +619,32 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 6,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/var/folders/_2/9y4tsvdd2n3gqjgd2zmlr1km0000gn/T/ipykernel_35862/935228866.py:2: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
+            "  fig.show()\n"
+          ]
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1200x800 with 3 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "fig, _ = plot_correlations(y_train_detrended, lags=60)\n",
         "fig.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -227,15 +660,36 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 7,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "deseasonalizer = LogTransformer() * Deseasonalizer(model=\"additive\", sp=365)\n",
         "deseasonalizer.fit(y_train)\n",
         "y_train_deseasonalized = deseasonalizer.transform(y_train)\n",
         "plot_series(y_train_log, y_train_deseasonalized, labels=[\"Log with seasonality\", \"Deseasonalized\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -246,25 +700,65 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 8,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 8,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "remove_components = LogTransformer() * Detrender(model=\"additive\") * Deseasonalizer(model=\"additive\", sp=365) \n",
         "remove_components.fit(y_train)\n",
         "y_train_removed = remove_components.transform(y_train)\n",
         "plot_series(y_train_log, y_train_removed, labels=[\"Log with seasonality\", \"Deseasonalized and detrended\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 9,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/var/folders/_2/9y4tsvdd2n3gqjgd2zmlr1km0000gn/T/ipykernel_35862/10449850.py:2: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
+            "  fig.show()\n"
+          ]
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1200x800 with 3 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "fig, _ = plot_correlations(y_train_removed, lags=60)\n",
         "fig.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -300,7 +794,30 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 10,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from sktime.forecasting.naive import NaiveForecaster\n",
         "\n",
@@ -309,9 +826,7 @@
         "y_pred = naive.predict(fh=y_test.index)\n",
         "\n",
         "plot_series(y_train, y_test, y_pred, labels=[\"Treino\", \"Teste\", \"Previsão Naive\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -336,25 +851,378 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 11,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-1e28d784-7ed4-42cf-8a67-6719a3703640 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-1e28d784-7ed4-42cf-8a67-6719a3703640 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-1e28d784-7ed4-42cf-8a67-6719a3703640' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Differencer()</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('09f41391-0497-4182-b259-4e0ec890fde5') type=\"checkbox\" checked><label for=UUID('09f41391-0497-4182-b259-4e0ec890fde5') class='sk-toggleable__label sk-toggleable__label-arrow'>Differencer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.difference.Differencer.html\">?<span>Documentation for Differencer</span></a></label><div class=\"sk-toggleable__content\"><pre>Differencer()</pre></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "Differencer()"
+            ]
+          },
+          "execution_count": 11,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.transformations.series.difference import Differencer\n",
         "diff = Differencer()\n",
         "diff.fit(y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 12,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 12,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_train_diff = diff.transform(y_train)\n",
         "\n",
         "plot_series(y_train, y_train_diff, labels=[\"Original\", \"Diferenciado\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -372,7 +1240,350 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 13,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-2bc8b6bd-51e5-49e0-9e01-f8baa9cb44c6' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>TransformedTargetForecaster(steps=[(&#x27;differencer&#x27;, Differencer()),\n",
+              "                                   (&#x27;naive&#x27;,\n",
+              "                                    NaiveForecaster(strategy=&#x27;mean&#x27;,\n",
+              "                                                    window_length=24))])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('edcb41be-e305-45dc-827e-4dbc0a289273') type=\"checkbox\" ><label for=UUID('edcb41be-e305-45dc-827e-4dbc0a289273') class='sk-toggleable__label sk-toggleable__label-arrow'>TransformedTargetForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.compose.TransformedTargetForecaster.html\">?<span>Documentation for TransformedTargetForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>TransformedTargetForecaster(steps=[(&#x27;differencer&#x27;, Differencer()),\n",
+              "                                   (&#x27;naive&#x27;,\n",
+              "                                    NaiveForecaster(strategy=&#x27;mean&#x27;,\n",
+              "                                                    window_length=24))])</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('0f441881-6296-42a5-8123-efa65324c02c') type=\"checkbox\" ><label for=UUID('0f441881-6296-42a5-8123-efa65324c02c') class='sk-toggleable__label sk-toggleable__label-arrow'>Differencer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.difference.Differencer.html\">?<span>Documentation for Differencer</span></a></label><div class=\"sk-toggleable__content\"><pre>Differencer()</pre></div></div></div><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('815d2d8a-5ed0-4a22-98d6-18f7cf7a7465') type=\"checkbox\" ><label for=UUID('815d2d8a-5ed0-4a22-98d6-18f7cf7a7465') class='sk-toggleable__label sk-toggleable__label-arrow'>NaiveForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.naive.NaiveForecaster.html\">?<span>Documentation for NaiveForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>NaiveForecaster(strategy=&#x27;mean&#x27;, window_length=24)</pre></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "TransformedTargetForecaster(steps=[('differencer', Differencer()),\n",
+              "                                   ('naive',\n",
+              "                                    NaiveForecaster(strategy='mean',\n",
+              "                                                    window_length=24))])"
+            ]
+          },
+          "execution_count": 13,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.forecasting.compose import TransformedTargetForecaster\n",
         "\n",
@@ -381,9 +1592,7 @@
         "    (\"naive\", NaiveForecaster(strategy=\"mean\", window_length=24))\n",
         "])\n",
         "model.fit(y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -394,13 +1603,351 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 14,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-3fc9a297-58bb-4679-9e8f-270e09aa8ed7' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>TransformedTargetForecaster(steps=[Differencer(),\n",
+              "                                   NaiveForecaster(strategy=&#x27;mean&#x27;,\n",
+              "                                                   window_length=24)])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('16fcc7bd-ba53-466e-9fd1-4862acf572ad') type=\"checkbox\" ><label for=UUID('16fcc7bd-ba53-466e-9fd1-4862acf572ad') class='sk-toggleable__label sk-toggleable__label-arrow'>TransformedTargetForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.compose.TransformedTargetForecaster.html\">?<span>Documentation for TransformedTargetForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>TransformedTargetForecaster(steps=[Differencer(),\n",
+              "                                   NaiveForecaster(strategy=&#x27;mean&#x27;,\n",
+              "                                                   window_length=24)])</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('952f7f96-c748-4889-92c7-470e475b0a48') type=\"checkbox\" ><label for=UUID('952f7f96-c748-4889-92c7-470e475b0a48') class='sk-toggleable__label sk-toggleable__label-arrow'>Differencer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.difference.Differencer.html\">?<span>Documentation for Differencer</span></a></label><div class=\"sk-toggleable__content\"><pre>Differencer()</pre></div></div></div><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('401e739a-4c96-4e04-a009-620015450a5d') type=\"checkbox\" ><label for=UUID('401e739a-4c96-4e04-a009-620015450a5d') class='sk-toggleable__label sk-toggleable__label-arrow'>NaiveForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.naive.NaiveForecaster.html\">?<span>Documentation for NaiveForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>NaiveForecaster(strategy=&#x27;mean&#x27;, window_length=24)</pre></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "TransformedTargetForecaster(steps=[Differencer(),\n",
+              "                                   NaiveForecaster(strategy='mean',\n",
+              "                                                   window_length=24)])"
+            ]
+          },
+          "execution_count": 14,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "model = Differencer() * NaiveForecaster(strategy=\"mean\", window_length=24)\n",
         "model.fit(y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -411,13 +1958,34 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 15,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 15,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_pred = model.predict(fh=y_test.index)\n",
         "plot_series(y_train, y_test, y_pred, labels=[\"Treino\", \"Teste\", \"Previsão Naive com diferenciação\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -430,7 +1998,341 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 16,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-6d8446ab-1736-4e5b-9fb5-49ade987d4af' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>TransformerPipeline(steps=[(&#x27;log&#x27;, LogTransformer()), (&#x27;diff&#x27;, Differencer())])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('e33c1dd0-d663-4154-9fef-64b3a169927a') type=\"checkbox\" ><label for=UUID('e33c1dd0-d663-4154-9fef-64b3a169927a') class='sk-toggleable__label sk-toggleable__label-arrow'>TransformerPipeline<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.compose.TransformerPipeline.html\">?<span>Documentation for TransformerPipeline</span></a></label><div class=\"sk-toggleable__content\"><pre>TransformerPipeline(steps=[(&#x27;log&#x27;, LogTransformer()), (&#x27;diff&#x27;, Differencer())])</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('67514a79-a590-4907-a1d3-686640ba293f') type=\"checkbox\" ><label for=UUID('67514a79-a590-4907-a1d3-686640ba293f') class='sk-toggleable__label sk-toggleable__label-arrow'>LogTransformer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.boxcox.LogTransformer.html\">?<span>Documentation for LogTransformer</span></a></label><div class=\"sk-toggleable__content\"><pre>LogTransformer()</pre></div></div></div><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('6d1651f8-8132-44fa-94c4-e82150f7e17b') type=\"checkbox\" ><label for=UUID('6d1651f8-8132-44fa-94c4-e82150f7e17b') class='sk-toggleable__label sk-toggleable__label-arrow'>Differencer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.difference.Differencer.html\">?<span>Documentation for Differencer</span></a></label><div class=\"sk-toggleable__content\"><pre>Differencer()</pre></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "TransformerPipeline(steps=[('log', LogTransformer()), ('diff', Differencer())])"
+            ]
+          },
+          "execution_count": 16,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.transformations.compose import TransformerPipeline\n",
         "\n",
@@ -439,19 +2341,38 @@
         "    (\"diff\", Differencer())\n",
         "])\n",
         "log_diff.fit(y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 17,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 17,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_train_log_diff = log_diff.transform(y_train)\n",
         "plot_series(y_train_log_diff, labels=[\"Log + Diferenciado\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -462,25 +2383,57 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 18,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 18,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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s2FBOTk5o2223jXoOoCtrze+hn22Arqa1voP77LOP6zaTJ09u9dcMdNXv4V133RUaOXKkeXxxcXFop512Ct13332hxsbGVn/NQFf9/6N2BJZA638Pb7rpptCQIUNCeXl5oR49eoQmTJhgAtDOIqD/09ZVngAAAAAAAACgWMMSAAAAAAAAQLtBYAkAAAAAAACg3SCwBAAAAAAAANBuEFgCAAAAAAAAaDcILAEAAAAAAAC0GwSWAAAAAAAAANoNAksAAAAAAAAA7QaBJQAAAAAAAIB2g8ASAAAAAAAAQLtBYAkAAAAAAACg3SCwBAAAAAAAACDtxf8H8NLffCmLWTYAAAAASUVORK5CYII=",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "model = log_diff * NaiveForecaster(strategy=\"mean\", window_length=24)\n",
         "model.fit(y_train)\n",
         "y_pred = model.predict(fh=y_test.index)\n",
         "plot_series(y_train, y_test, y_pred, labels=[\"Treino\", \"Teste\", \"Previsão Naive com log + diferenciação\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     }
   ],
   "metadata": {
     "kernelspec": {
-      "name": "python3",
+      "display_name": "tsbook-py3.11",
       "language": "python",
-      "display_name": "Python 3 (ipykernel)",
-      "path": "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/share/jupyter/kernels/python3"
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.11"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 4
-}
\ No newline at end of file
+}
diff --git a/notebooks/part1/03_ets_and_ar.ipynb b/notebooks/part1/03_ets_and_ar.ipynb
index 4713a82..cdfca3f 100644
--- a/notebooks/part1/03_ets_and_ar.ipynb
+++ b/notebooks/part1/03_ets_and_ar.ipynb
@@ -25,7 +25,20 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 1,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "import matplotlib.pyplot as plt\n",
         "\n",
@@ -37,9 +50,7 @@
         "ax.set_xlabel(\"Observações passadas\")\n",
         "ax.set_ylabel(\"Peso\")\n",
         "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -50,39 +61,392 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 2,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from tsbook.datasets.retail import SyntheticRetail\n",
         "from sktime.utils.plotting import plot_series\n",
         "\n",
         "dataset = SyntheticRetail(\"univariate\")\n",
         "y_train, y_test = dataset.load(\"y_train\", \"y_test\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 3,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-e8e9fde3-c53d-4f92-8aa0-3384c3e072e0' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ExponentialSmoothing()</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('5df56545-6651-446b-b828-34bb50e1cf83') type=\"checkbox\" checked><label for=UUID('5df56545-6651-446b-b828-34bb50e1cf83') class='sk-toggleable__label sk-toggleable__label-arrow'>ExponentialSmoothing<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.exp_smoothing.ExponentialSmoothing.html\">?<span>Documentation for ExponentialSmoothing</span></a></label><div class=\"sk-toggleable__content\"><pre>ExponentialSmoothing()</pre></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "ExponentialSmoothing()"
+            ]
+          },
+          "execution_count": 3,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.utils.plotting import plot_series\n",
         "from sktime.forecasting.exp_smoothing import ExponentialSmoothing\n",
         "\n",
         "model = ExponentialSmoothing()\n",
         "model.fit(y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 4,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_pred = model.predict(fh=y_test.index)\n",
         "plot_series(y_train, y_test, y_pred, labels=[\"Treino\", \"Teste\", \"Previsão Exponential Smoothing\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -93,7 +457,30 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 5,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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msYZl87Umk+ce3KOslnaLTkivWf1+02OCkcAyet1WbYl2CCzfffddueqqq0wLuN3QoUPlhx9+aOEhAQAAAAAARGjVZLMZ1QGR62d/ldQ28WiwOeyG1yXjkhfNz7Ab3/Addup2E2fOkfwrXjKXHTkkDddVNP0eCvl6jFYZ5g4+JHo9mFMsGYWDZf0rp8nKRyaZUM978E5kfcxE07YbKteay7rN3ySusIzREu61JqYns+5mwHdgmWjtzUAwy/m4DGdOhjZuCQ+FQtLQ4Bw/r1auXGlawwEAAAAAANJBW7ybjT4JiyxZvy2pbWKxqjPtlm2uMrc9fcZucdvKrcdaYalV2Znocalqadt7qNZWYem1RmQMmQV9mx5Ws1mkZkuk5XvDQlk360Sz1mMgM1/C9ZVmm2BeH9nuoHtNy/nmkpFmu5ihYmM7tbjavcOhhpgt4fbnirDH1W62+zSwDDffrzlmj8AyUdgqGVmOVvJEFZbPfL9Arv90tiwpWy+jivrI1O1HyewflkSv/3biVDl26Lj4z9lNpFRhOXXqVLnjjjui1wOBgGzbtk2uvvpqOfzww9N5fAAAAAAAoBvTYM5dE6fVk6NKeyS1TSwXv7Ao5n2JKjRbWtmZjHS0vYfrtsVtuY4l5AgHzaNtl43DdRqH56jCMadF18f0nrbt52A9gsXGCstgTs8Yx2MTDRJt94VqPSeaWyFos12YVvfY7ebWGpbqtczhsv935ZL/9ytkl+dmyuUfzTKX9us/eethWbB5tdQ01Mvnm1fLrQvnRK/rpd6voSZSDCxnzpwp//nPf2TMmDFSXV0tP/3pT6Pt4Dp4BwAAAAAAIB20itAeR5mAMCyypaou2oY9dVSpZ4XljEO81lZsomGfVlPGkqhCsyWVnclqaTiqrdtb59/TdJy1Te3hiYTrq+Pda4br2ANGe3VkdNp2MEuS4lEBWrNuvrlsqFjTdGMwS3ofcKdju5J9b5ZgZoHnbq1hQVmudTdXPbFfszUrrbD1tcwRckSPk2VM0f+aSw0n9eegzf1lx+rJsl+PM+ScgiNkcXV9zDBSr3vVgdrfT3XJR8/7Oz9dXEot4QMHDpTPPvtMHn/8cfn8889NdeWZZ54pp5xyimMIDwAAAAAAQEtoy/M1U0fKNY3BXGmPbFm7rVaWb66KtmF/vrpcLpkyXG6d863Zpig3Ux48caIck6BdWkPAeBJVaGplpz5/OIXKzmS1JBzVIE5bt+1CtVvM7e5J2F7Cde4Ky+bDdWo3fRGzOlKfIyNvO2moSKIa1BVY6rFWLHncutfx/AU7Hi8b3zo/ekv+0EOlbN7tnvvVieSR/Tcdo4aPd9WMk6XvvC0j582Xw3bYI9qqXdrnEllRWyuBcFjCgYB8lbGdCSfNM9eHJSwBWRVsHBzkfg0xLuNZtm2LqbLs7q3hmSk/MDNTTj311PQeDQAAAAAAgMukgcXR33MyMzwrDV9fsj66zS4DeiYMK60QMJ5EFZpa/ele/9JPZWcqWhKORobHNK/v01Zur8BSw0F9jK7hqG3RiSosdbjOupdOarrFo53bHUDGFMw01ZXulvWY08bD9c1axLVV2xqAY8LI3D1kabBEhoU2yyEr1sjrPU6WpeESGdZjs+xXt1z+nDspGkgurKyQhbZqyBWNL0Xvi7zaQORNtt1m3og0uv6z2QSWfk/WCy+84PvEHnXUUam+JwAAAAAAAA6VdU0B2PItzVu43ZWG73y30bSKJxpK4xUCqqyMgDx+6qSEoafuWwfs2EPLf52xm6+wNFnucFQzMr/haGR4TPP6PtPKHbMaMxLZuQfm5Gy/r9T88G50Yvh2hzwg+cOP1kSyaSde4WSoztfr1DUhwzocyLUPrwE4Vhj5/T9+I8N6nCLnVc81t9//76fkq+CR0rvHNlmV0TMaRi4JbidLNtWKBLczJ/ArvZ7bx5zIaPjYuGZl3GrINAeUbl9tbQrfuyvfgeX06ZHFUhPRATxeE8QBAAAAAABSoQFk/CxCpG9hTnQ9Sr8Tu70qJNVjp+zqO3R077slYWWiKeA9czNla3UkyBvYM1fuOHpnX8+XGWNSt7ZyJ67GdD4moBWQjfKGHmaG67gnevuvsAxIMLdEQtWbmm7JyJGwlJvt7VO1NZDct3qJvJM12FRLbheqaAojw2FZEuzV1Kq9daOEJaOpVdtRCRmOBo5hK/VNNoBM5TE+BSQgo3qWSnfnO7AMhWxJOQAAAAAAQBt5doFtyIqHxg5d5222oTSxAkurQvKURz+Rmvqm3EOH+CQTKtr5qeyMtV97eKrrcup1XZtzryElzYLVFVuqE66JaLV215n1JZtvra3cfqsxLQ3bVkZ/D9WWRX5xB5SuANOrwlKrI+/pMUW+C+fL0MwNpjVbw8jvg71kaMYmOXBrrtz31sPR6PRL6SFf5k6KhoXuMDIaPiZs1Xbdlkrw2IoVlroq5m8nHiLdXSCsMTTiKisrk549e8rWrVulqCjyhQAAAAAAAG0j+7JZUh/yji+sATsaOlbbQkdLbmZQKn8fqbyLZfD1r8vKrU3rNI4u7SE3/Hh0s9DRChWtEM1r6rN1W7zKTi8adGpI6WVISV50yJD9ecb3L5L5F+/v+Rh3a3dzARl2QU2zW1c+MsmzGjMqI0ekoelxGYWDpdc+N8r6V06L3tZjp1Pl3VEXRqsjRxX1kT3XzJJ3Ml3VkSaes1U5Nl5aLdzNj9w66y3QitWRLaVH9dSBZ8gxQ7rmwJ1k8rWUh+5UVFTI22+/LcuXL5fa2lrHfb/+9a9T3S0AAAAAAIBD7/wsMxncy77Depm2aK12dAd+vofSVDmr/5as2+bZTq6VlbGbpf1XdiY7AMgdVlrPE29CeKxBO/Y9aA2bLu1nV6IDdBwTxV37aKhpNshmv3/fL+/oIJvG6wduyXFUR36+ebV8nuNRHWmFj67W7EiFZGOY6RBoeRjZQcNKNb7XgC4bViYrpcBy/vz5cvjhh0tlZaUJLnv16iUbNmyQ/Px8KS0tJbAEAAAAAABpoy3Rzy9aG71u6/6VV75cZ6oTDx65nSOwTGYoTUVtg6/QUUNFP22q7iFAfngFrnbu6FGvxwtjE7V2Rw60QafcOG56LXOEXL3defJNbYMJHy/MWiUN5SujAaVj7UhrkE3j4JroIJtKj8E19jDRKzRsdlvHatVOKihNsYqTVvAWBpYXXnihHHnkkXL//febUs65c+dKVlaWnHrqqXL++eensksAAAAAAABP2/fMi/4eDIj0L8yVH8oiLdzaKa4Ddtxh37h+hXL11FFxh9Joi/e1rzWflB0rdIw1VdzNb2WnnwFAGnsNLsmLDhSKHp/ED2NjDdqxV0eOev4OOXTgaJn9wxLTut0vt4csq9hiBr+EA5kmfDwr1EekYEI0oPQcZONRHZn0WpEduFU7IffwnkBA9u07TN5duzS6yeEDd5KXV+paohF79hksn2xcKXWNM2P65vagurKlgeWnn34qf/rTnyQYDEpGRobU1NTIDjvsILfccoucccYZcuyxx6ayWwAAAAAAgGah4mPzf4heH9mnhzS41rO0KiLtUzr+e/5+kp0ZjHk27etR+g0dY4WKbn4rO93ys4JSWde0DqcV/Z0wYYD8Yc63zZ8nzkCg0/scIxNzKp2t23XL5c+5k6Lh44Ita8yPRcNK+359D7LpTNWRaaqGtBtfv0aWZGwnNY0xW4nUyj59d3AElgcN2NERWO7VZ4h8XbZBNtVUmuvBQOzPaneU0tnQakoNK5W2gOs6lkqrLVesWJHeIwQAAAAAAN2SFSra15j8ct02+XZj8/Ue3SOFK+s8JlXbuNej9BM6anv4n44fH72eqeWeHoaW5MWt7Iz1Ou1hpTRWVv7rjN3ktSXrPFdz1JZ19z60AlSHD/152wA5p+AIUyVZ21gtqWGlvrBo+OiHbuunOrIjch+XVzjp8dpygk31fT2zc+W04bs67j+55nPH9XEN66Q01PSZDGTmy7Y650CjdVXOat2K+lrzY6ls8F6jtbtKKbDcZZdd5KOPPjK/77///jJjxgx59NFH5YILLpCdd9453ccIAAAAAAC6IStUdPMaGO7eripBYBlvPUod8qNBoVfouP/w3pLImvLm07dTeZ1ry2vM9HOvNnT30B13ANuj7xfRSkqzvbtt2S8/YWQqFYrpCDm99mG/zV12q63add87Np/iun5Q/x1lbEnf6PVQOCzDCp3veb+wMzCvzi6WqkBW9HpVOOAII9W6amdgWVZXIzUN9dHrFXUEli0OLH/3u99J//6RL+2NN94oJSUlcvbZZ5vBO9oqDgAAAAAA0FJ+h9yocJKBpa5HGcumyjq5dvYSU7UYb0BPSV6WZ+VjsutXxnqdWimpP173uZ8nuo/C9SLDP5Zt2aHmlZSBDtSqnWzVpp9qSdd+d6zfIPnSVJ2bGW6Q/eojXcKWaT86z3G9T14PZ+VjfV2z8HFjoGlNVVUdzJXq7JLo9aqGOil3VViudwWWG1zX68MhqQvF/8x2JykFlmPHjpU999wz2hKuw3euvfZaE15OnDgx3ccIAAAAAAC6IQ0V/cZl7vbsKld7tdvUUaUx79NoTKsatcXaHVpW1DZVxW2sqPWsfEx2/cpkXmes5+lbmGPCysDgxSI5Fc2rCzsSPa5Ex+ZRHTm0YbNjk/3rmtaIVL8cGcmqLDuEt8iODZui1+sDGVJhq4T0qnys1FZtW7VjQzgkm2qcA482uQLLirqq5qFmjbMKc0O18/p613XrudGCwPLoo4+Wv//97+b3LVu2yF577SW33XabTJ8+Xe67775UdgkAAAAAALooDf0mzpwj+Ve8ZC69Khe96JAbP5GbZlsjtnNWTFbaKiG9zF6yLu791iAf+zqRkcetj/7uFYmeMKF/UutXJvM67a6ZOjL6PHo+zRTx0mXOwsN2m7rto1U7wbGZMNK2ja4TOSRgCw4DAZlcv9LxmO0LejquV0umVAUy44aN7uDQq6JyXbVzAv3GYL7j+tasEgm7XrN7v1Ywmh3McFwvzMqRjMaBO/rcaEFg+cknn8i+++5rfn/66aelb9++smzZMhNi3nXXXansEgAAAAAAdEGXzVpsKhU/bxwGE6ty0YsOuXn6jN0k1zbt22vOjWZh5+w9NKmW8C/WOivrvOh+7etEqn/Mc4Zkbv/6fE1Soaz1Ov95inOwi5v7Ze85pKT5GpjZla2fUfqq2mx+EAFboLdT/TqZVNc0+V2d5Bpk4w4je2bnSWXjFG7f4WMgy7G2pNoYyI/bqm0qLF2Bpbs60t0SvjmnT/R3K5C09luSnee43iMzx1yurSqPVnCGG8/pDk/dKLkPXya7PDdTnvl+gXRnKQWWlZWVUlhYaH6fPXu2HHvssWZquFZaanAJAAAAAACgod2tc75tXrnomnCdKMzboXe+Y+DO9J37Oba555id5YDh2zluq6pviHtcdV6Te1w0/HOvR7lqa3XcxzSEw0mFspaymqZWcy/uo61vCEcrVzUMNvfX5rewCzyFVm0RGV/UFJ6qA4LO1u2fDRrhCDF7SJ30FOcaj33DlXHDSA0rqyTDuU3Quc3q9UuaVVhWSlbcx7gDy7Laaql1rSVpBaFWGLk5o8hc9mxcH3ND41uXFQyaAFKtaQwk8zIjz2+tabmp1vk6tarSWqVUn7cuFJIFm1fLT956uFuHlikFliNGjJDnnntOVqxYIa+99ppMnTrV3L5u3TopKoq8aQAAAAAAoHvTyj8v7gnXidTUO5uv+/TIdlzfZ1hvqXcFkPEqLGMdV7PjDDdfj7K0R07ix8VoJ49Fg8eznnZWGLrtt0Mvx/V3l240oaiGo1HrhjgrLBMNrmkmcav2XnXLJWiLT0fk5cvOhc7Acu/gVsf1gbl5jgFAXpWP7oDSHSxW6jqRrsDSXS25ZuPXjuvaDu5uCXdXR66rinwOczMi2623rT3ZKyffsU1hY3Xkeol8/oLZkQxsW30kjNSwUQNru1WVZZKssHknAnL9Z7Olu0opsJwxY4ZccsklMnToUDN8Z/LkydFqy1122SXdxwgAAAAAADohnVwdSzKTtGsbnIHl5sq6ZuGkhkV+17CMd1xuYVewaB+6k2w7eSzRlu443Mf8+PxV5jH245ta962cVf1R0wH4mBKe2bh+ohrWo5cc7MwA5aQaZ5Xf5IYfJMP2rNnBgFQ0ON+PjWFnsLi+pjJh5aM7SHSHkVXhYMKW8A2uYNsEo43Pk9O44qi135LMTMdakgWZ2Y5WbbWtsSrSCiQ3uqojN9c6h/GkU1jC8tXWpvVSu5uUAsvjjz9eli9fLh9//LG8+uqr0dsPOugguf3229N5fAAAAAAAoJPS6dexJDNJu7bBWbX2ypfrmgWW2iJtd8VLX8RsyfY7ldteJan70orGLdX+AkuvdvJ4YWSi2sd125wt1KvLqps95tdFT8rk+hXm9x1Dm+THtV/Fnap9TL/B0SpClRXMkEHb7+HYpjTsDEq3BbKlLtAUSFY21EuFa1jMxpAzWFy5/N2ElY/uikp3GBnvMTnhyHuyKSOyfGGvxjBySyA3WtlpVT5awWh2XSSYtNar3OgKVZW7NbwtBSQgo3rGnmTf1aUUWKp+/fqZakpdu9Kyxx57yOjRo9N1bAAAAAAAoBPT6ddeLpsyPKlJ2uWu9R0rXNWTGli++fUGx20rt1Y3W0fSWvNRB+7Yw75YXdD2Kkk/VZD2/Xm1k8fiJ0ANug6yX1FOs8fskLVK8iVyrjTcGxDeFneQzeC8fMeAGa+BM+5Kx2ZBYkODCS3tNoQCcSsfteoxUUv4RlcYWWWrlrQCSesxeeHGtSQbW7Ub6iPhY2WgaemAeisCazyPa13P15EEGissfzvxEOmuUg4sAQAAAAAAEg3M+esJExy3/fHYcfL7aWOSOnFVcdq7zf31IfnbR8t9VUjqmo/2gTsaDo3vVyRDSvKaBYD2Kkk/VZAW3d+/ztjNdyirwW6ifbvX6Jw2pm+zx3xXN0ByQ3VNoaCrhXpj0Bk+amWkDn2xVDbUSUVj+3PMtSXdw3AaQs0qLDeEgnHbvTVMrWgMH3Mbw0YrGI0VRpYHcqKVnVaLdkVjILnFVZ25tTG4dHCn0i2bTtSqxvXqL08feIYcM2ScdFcElgAAAAAAoNVsrnKGWdVxpnfHkihaqq5rkBVbqnxVSLr3VZyXJfMv3l9mHjW22X32Kkm/beS5mUGzv2QqSDXYPXmX7SUZEwb0lKfP2C16vTg3Ux5tOEXyA5GKxOpAplnDMV5wuKlW28qbXrVWV1bUuSosXWGgex+VoVCzCstNgRxnq3bjY0pCkfeoOpAVDRutykdrv1k1mx3Vke4wUtWG0xBnJRgu1Fr65RVKr+ym4DgjEJQ+uU1LJ+zSa3uZf/TF3TqsVASWAAAAAACgVWhV4yUvLnbcdtELi2OuLekl5Kos9FJVF5KBPXOb3e6nQlIDVT0eDQ01AOxfGAnbSvKyHFWSiaogrfhru4LsaOt5/hUvmUs/r3dYr0iI9ePR/tYtrGsIyfSx/aLXDxtdKnPD+8oTZQeb6zrUprJZ2OissPxhrXMyeU1DvZTXVSdo1c53VEZq/LypcpP5vVco0oq9qfF58sOR8HNT42Ps56+mcT3K+oCrVbtxHcqOGDYmEpSAlOY61y0dWdTHcX32of9PBuRHpour3036sVw4dv/o9eLs5p/j7ojAEgAAAAAAtAqvdR/1utWmncqEcLvsjGB0DcsTJzavUPRbIWmtdamh5RUH7WhuO2RkH0eVpBVo9sh2TsC2DCzOjQaJVut5dX3IXLrX0vRSWRepPB3Xv8g8T8BHi7h9Lc9w47maXz02cj0QkK1ZJfGnajc0f5YNjVOzo2GjqzrSup7fGFiqjZITHchjXktjZedmVwu6V7VkU9Tb8Vu1R7nCx+GFvWVoj6ZzfOm4A+TinZvCx/El/eWNw85yPOaDdd/L0m2RgFd9t22TLC1vuj5v4w/yzPfOyezdEYElAAAAAADwpCHbsBtel4xLXjQ/w258I6nqSK+qRr1utWnbnydWRaI9sMzLcsYYocZw63dvfh393dKnINt3haR9rUvrOTQEddPQcnSMyd/3HBNp4d1UWedoPQ+79h9LZWP4mJ+VYZ5nXP/CuKFlXUNYymqaQkMNSmvqQ1ITaqrQ2xjO8Jyqba0LGQ0jpWk/66ojU8FrJcNRHZltG34Tvd11zq3HtCh8bLPqSdfnJbdAdujRK3o9IxCQ/nlN1Z4D83vKv398tuMx/zrwZzLU9hitjtQA0vJt+UaZuXCO4zH/7/2nHYON/vTlB/Lnr+ZGr5fVVctP3nq424eWBJYAAAAAAKAZa0jNsi26zmEk3lm2ucpXtaBFqxrdNI6y2rTtzxOrIlFDOMueg0s8B9GsKa+RW9761nHfabsNbFYhecjI7TyP077WZV5WhqPiMdHEckvP3EiQpwN9vNbCdIe0blZAmt9YwZmoBb0+FHIcS1l1vQl3q8M5khWO7Gtj4/CZ3uFqxzqRVmC5uTHArAuFouFoVeN6lNGp2o08W7Xd4WKi6+1Ej6J/dqQK1AiHZUzPpnZ69fiU02RYYe/odW3Tvn7Sj6PXi7Pz5O013zkeM3fdMjOoyPKHBXNMAGnRYPLOxe+mdMyXfPS8dGcElgAAAAAAwLOdOxa/Ld0aurlpCGe1aVvPE68i0aqwzAwGomGil4BHBaKdBqCvf7XB+7G2tS61wjFWhaUqixVY5kXWZAwGmh+Lff+xVNTWO55fA9arDo60p+v+inIzm1dYVjcdy5tfb5Dy6nrZlF8rDY1HsLkxsMxunByuw27sVZOWbcGc5uFoR5qq3ey5ndd36ulc9zMrGJQemU2Twn+24x5yzajx0eulUiWfTL/I8RgNJO2Vj498O09eXNa0/upXZevlp28/4njMWR88Lf9d3zSdflNtZA3PdFi+bYt0ZwSWAAAAAACgmS/Wxq4I/Hx1ma+BMhq66Y9dRkDk2tlLoo/zbBu3VSTW1kfuzckMmgncsbj3YVVf+glg7Wtd5iUILK2qRg0m7YpysqLBarxp44lawgtsa2TqOppqxz4Fst+w3tHzYL2+mXOaqkpNFWzhetkwcLU01UtGrPYzyCaR1qqWdIeRruvBcEgKGtfTNNclLIMKmipts4MZ8tn0SxyPeemQX8rhg8ZEr5dk58nXlZFWd7UlkCNXzXvFDMmx3P/l+zJ3/bLo9TVV5fL8ioXR67Wh5KfbI3UElgAAAAAAwEHDRG1tjkXv8TtQZkiJc9CKFj5+3vi4nMtmeT7GXpFY09AQHbCzvqIpuGr2GI+WaTsNRmM9zr7WZdMaliHPieXbaiLHE7QFeBpS2oPEJ07bNXpfcV6mY/+xVLpawh3t6bUN0UpTqwJz4eoyeepz13kvXSYBDfw6SnWk1/PabtNjHRAqd9w9MrTRsc3tVa/JQfVLo9ePlVVy7+Rjo9dLcvLl+eWLHOHj/I0/yOaapmrHv371odz6bVO1ZG04KLcunCMhW7T8568+lI5ksG2YT3fkrCcGAAAAAADdXrxqRDvTvt3YIu6upLRosBmLhqLuYNS0h4dFpo7sYyo4v1wXqbTUoTqL1pTHPZZ4LeG6nqYGpW5j+hU6wsR4FZb/nL/Ss4JTf3/9q/WNxymytaqpVTsgzSsulYa8ep41SNVjsyZ+W4Gk+1h0qI65PztDNlfVyXtLm4a7RGVXmungbVodad+36/rw0CZZGiyRUCAS5maGG8x08bJAZDDQwcENclLl+3JmwdHR+1/a9pjsVvT/ZGtjO3vPcLVsadxevRnqJYHPXohe31hdYYbU2F3+sTMI31oXWcMzSo/RK9jtQGbucZR0Z1RYAgAAAAAAX9WIXtxTv90Tv79cGztk9KLh3aVThssf5nxrKjhrG4PHrdX1srW6acCJ2y/3HOy43tAYKFrHEyvsvNrVqm2varTT/Zz+2Kcxn3/m203t2b96+vPo7xouuqtQvQYNfbux0qPCsqna011hqdPIm6nNj1RYpkX8/eiR9QzXRK/r8w4OONdwfHrbU45tbq2aLcfUfRm9vl2fMfJFsGnQjbay35LzI6lsXGtTPZc5Wt7JGhq9vjmQK0+tb1qLtD4cOxCPq53CSutZh/QokdyMTBnfq79csvMUc2ldf/rAM+SYIZGp890VFZYAAAAAAKBZaKghmt/oy2rftoI4a4hOMvuw/O3EifLTRz8xv7sfGytiKszJlAZXULd0U2X0eGLRVu7jJwxw3BYdulPvDCzdw4Hcvt7QFPK6t9Ns7OLnF0UrKq0w1T5oyPL/nvpMfj9tjKlYjVZY1mtLeGQrK7h0v15j3RAJD17c8upBDR9DW2V5RnH0ptFFvWV1VUW0WvEPI8fIwgWPyoM5u5jrU+q/l4ty18uRDXtE1558L3OQbLOFj18He8m6QNPAnxc3bZVteftEr4cCAflz7iTHoTyXs5Pz2DpwVaTYwsi1VeUysmcfmTFxqnk7rv9stny1dX30NncgebNMa7fj7YjatcLypptukt13310KCwultLRUpk+fLkuWOMvOq6ur5ZxzzpHevXtLjx495LjjjpO1a9c6tlm+fLkcccQRkp+fb/Zz6aWXSn29c2rXnDlzZNddd5WcnBwZMWKEPPTQQ23yGgEAAAAA6Gx0uncyQaM1UMZr4neybn/nO1m2ucrzvlgBZklepvztvysc92nL9Nm2Ske/mtqwm6+BGe/1jO7TNAXca+jOsi1V0YrKeOuDaqWlVZFpHYs+/uMVkanRsc6Nmlr3rdxb8ZLk24bURHdgUxraJj1DTfvJDASlT25B9PrEhjVyd+Urjse8d/g50i+/aXhPSU4PWW8LH+dl9JdHw4Mc5+C8giOkTpoqRu/N3VNeyW6qaN1mm8od4RFGpnP9zQQDftJVHfndT34jFaf/XuYffbEJJo8dOs78br8NHbjC8u233zZhpIaWGjD+3//9n0ydOlUWL14sBQWRL8qFF14oL730kjz11FPSs2dPOffcc+XYY4+V//znP+b+hoYGE1b269dP3n//fVm9erWcfvrpkpWVJb/73e/MNkuXLjXbnHXWWfLoo4/Km2++Kb/4xS+kf//+cuihh7bnKQAAAAAAoMPR6r6nz9hNfvbYfNnW2BrdIzsj+rvdZVOGR9eATBTq+fG0e5CMjQ660bUsrfBocEmeCfA2xBjGE29Ij7X2pLaLa0BrrcH5xteRtSi1CnLCrXPk0NGlMnvJOqmJsxanmjF1pJz4j3nNppPbhf2uCxqIrAta31hN6fexvy56UkbVLZNTM/vKAzm7RVu1h4Y2y9KMXtHtntuuXE5fny1bJTIQ6arAl1K+dYvMzIlUR2ob92cZfW0HFZabFr4tK7ZFQlP1wrrVMit7VPR6WSBHHg81rQUatuK9llZEprOi0r52ZbQKNbISq/Ub1ZEdQyAcbq9RUc2tX7/eVEhqkLnffvvJ1q1bpU+fPvLPf/5Tjj/+eLPNl19+KTvttJN88MEHstdee8krr7wi06ZNk1WrVknfvpEv0/333y+XX3652V92drb5XUPPhQubxtGfdNJJsmXLFnn11VebHUdNTY35sZSVlcmgQYPM8RQVFbXJuQAAAAAAoL3te8978p/vN5vfe+dnyZ3Td5ZT/zk/ev/fTpggP9ujae1IDf9itYFftN8O8qe5y8xwme0KsmOGjH4dsVOpnLP3MDn8Lx/GbdVOxHqsBrQqXgt5vBb6Ly8/UDIvfdEM3UmH3MxgzEFBsSze/iTJCdTJ/TmT5Nbcvc1tE+q1WvJl2a/of6Lb3TOgQC79YYtUNbZrn17zqdRIhjyRE6n8yw3VSnUwMvTG6IgDalI4pl9WfyzvZg2R74IlskNos+xbt0w+6L2/fFNdE7NVG+mj+ZoWI/rJ1zrUGpZ6wKpXr0jqP2/ePKmrq5ODDz44us3o0aNl8ODB0cBSL8eNGxcNK5VWTZ599tmyaNEi2WWXXcw29n1Y21xwwQUxW9WvvfbaVnqVAAAAAAB0PO6p1Vp1aK2baLVIb3YNeql1pXP6GHvgZw8S9x/eWxavLZdXl6w3LeS/fq6pqCgV73+/WfYYHFljMSsj4DjWZNgrGsNJxJ59CrKjFZwDe0YqFdMVVurx6LqgSxonpPv1Xd0AGZ21TH4INLVuf53RS/6aHVln0nLuqgpHJPT3nImO+6tt605GDyg6E76duCsjbWGlV3Xk1AGjZPaqJY51I6fW7S1b5t4odZuXSFbJKCmecpUUjJjefq8JHT+wDIVCJkDce++9Zeeddza3rVmzxlRIFhc3LfKqNJzU+6xt7GGldb91X7xtNNmtqqqSvLzIHyyWK6+8Ui666KJmFZYAAAAAAHRFXsNy9PqQ4qZ/L1fWNch5rpDxrKc/l282VJiWaSvoPGF8f3mysa1bW7Y1BFy+udqsx1iQHYkh1m5r6mpMlU7fvvq1r8zvRTlZsqGyecWm38pLzcDsk879OPtHQ+W61yPPP+fbDaa6NBhoeWhpZXIa6l47e0lSFZZ3lZ0g0/s9I4/ljI/eVilZ8nDuLt5PFKta0bNysY3DysZj0pb2cCAg24fKZH2wwFRG/rr6Qyna7RK5Ze3WJAfZjJOCEce06ctAJw8sdS1Lbdl+77332vtQzGAe/QEAAAAAoD0qG631FNtKrGE5K7ZWJQwAb53zrSPotAdsP2ytNiGeys0KSkF2ZADL2vKWB5b249F8bcrw3jLn243R2wb1zJUVW6t970crGnXVPL8B4bcbm6aCa0iZykR0y7Hj+skzCyJFV+P6FcrVU0eZdUE/WLY5qcBydvVe8mG2K3j10zadznZvr1btBO3bOrjGqoYckZstkze+42jd1oByav13ZtuMgn7S+7C7TGXkyek7anQwHSKw1EE6s2bNknfeeUcGDhwYvV0H6dTW1pq1Ju1VljolXO+ztvnvf//r2J81Rdy+jXuyuF7Xfnl3dSUAAAAAAO1d2ajrKbZlaBlrWI67WjBWIBdrKrh9AI2Gb3mNgeV6W4XlQTtuJ29+vSGl47b2XlUfWRdTHdi4v0EleTJ9535y93++97UfrWgM+1zDMi8rKG994zzmlhRW6nutgWV2RlA+vXhK9LOhYXAsmcFA9PwWZAelojYyoGdrZlb6aiHdQWO8MNLeqh2jOnJU0XZy6JCJzVq1tTLSqoZc+cgkqatZKJfXvB/jkPQ1d5hxLGglQWlH+iHTsPLZZ5+Vf//73zJs2DDH/ZMmTTLTvnWqt2XJkiWyfPlymTx5srmulwsWLJB169ZFt3n99ddNGDlmzJjoNvZ9WNtY+wAAAAAAoD14VTZa6ym2pb6Frd9l+NtXvpRVjRWP67bVOtaCTJUVnVXXhWRbTb35vWdupDarviEsb/gMQrOCAVPRqMHhUWOdS8p5mbR9T8drSEd7u1WFav9sxGOFlRqeFuemfg7jssJH5ZiqHZk+rjSMzA7Xy+jQBvljxSy5t+Il87veNkpvq3xF3t72sCwu+6O8WPG4zCipk/lHXywVp//eXLrbuOs3fxU3kAxVrpV1s06Uim+ebZ3XjA4hs73bwHUC+PPPPy+FhYXRNSd1YpBWPurlmWeeadaT1EE8GkKed955JmjUgTtq6tSpJpg87bTT5JZbbjH7uOqqq8y+rbbus846S+655x657LLL5H/+539MOPrkk0+ayeEAAAAAALQXr8rGVNZTbAmt5Fu22dn63Rp0KM6Li9c2W8Nyk2uQjzsns0weUiwfLNviuC1sC++2VkcCy6LcrOht326sTHhc+lxj+jUNqXnu53vIZbMWyx3vfOeoELXLyghK/6IcWbHFX8u578AyM+j4bMRjrZeZk5nhXBO0Lkck26Pl3k91pOsy1lTtryvKZFhok6NV2+7Qbd6VofWbvzZhY+m0J2KuJZlZMlLqNixMUEUZMMNzWI+y62rXCsv77rvPTAafMmWK9O/fP/rzxBNPRLe5/fbbZdq0aXLcccfJfvvtZ9q7n3nmmej9GRkZpp1cLzXIPPXUU+X000+X6667LrqNVm5qOKlVlRMmTJCZM2fKX/7yFzMpHAAAAACA9qJrVnrR9RTbusrTj4NHbue4fsKE5NrWreexKi3V7K/WNwvixvZtChAt32+KH6rOWxkJM4vzIoFlXSgkQ0ryfA+4sbtl2hg5d++hMR/31rcbZdLAnpIuW6KBZaRlPt5nw2IFuhpyangatWZ44waxU2Cv6kgNJ63KSL28r+5dmXnI+TI7d5F8UfFXcznzkAvksxOulfX77ieztj3mGVbGF46GjbGU7HWVj5bvsJn0ja6rXSssI+sOxJebmyv33nuv+YllyJAh8vLLL8fdj4ai8+fPT+k4AQAAAABoDVNHlXoOVZk6sk+7r1/p5aPlzgrHEdsVSEZApMHnDqzNqusj6y162X1QsTzzs91l++ted9y+LsFkca3gtIeh2hJ+xm6D5KpXv2y2bZYedFhkTN9CmTF1pGkHd1ed3vHu0rjP9/kq/8NwEtlSVd+sJVyHL8VbT9M6lzmZQTlhwgD5g7XeZXkfkRVjJLzdMsnOr5adSkrl/4aPkY1zLpK7c/fwHGRjcawbGcgwFYxeVYx6m1ZJbnj9/0moxvmZSCx+2Kj7Lpp0kZTNuy3OPgKSVTIqyedFZ9KuFZYAAAAAAHRns5c0zWOwe/LTVS3arwZuE2fOkfwrXjKXej0WreTzW2FptV1bfvfmN77DSr8qahvk+YWRJePs9Hn8HOd7SzeaS23n3m2QdxWkhpl1obD81iOs9Ft1utI2Qf3KA0dIS2z1qLDU9TQvmdJYLdnI65i0wlInpNsrVMcXDJd/7XuWVP/sZrNO5PRBo+XQ+m9NVaSuJemnOjKYFb/KV4PFnAH7+HyFyYWNVctej/t4DT2LTSUmuioCSwAAAAAA2kmsdQqXbamKGzL6mTyulZtayaiXel3XZfSilXwdaeayVlLe8a53mGYNJYpnfeMwnLqGkAk/4+0n1nCjRFWnegi9bcOCnvpsVVLDg7Qq0s5as9S+hqXVmq4T4yf0LzL3je9fJDcfsZNrXxmSm9UUdJ6552CZf/H+jiC2asVbkrRA/MhIh95ULZ2V7E59hY2RwTvesrcbJ6XTnpSCEdOTfG50JgSWAAAAAAC0k3jrFKY6KTzWdOlb53zrGYJqJZ+GYgXZkdBL133UydPtRadvfxdnWM7g4jwT3ulPvOxy5dZqOekf82LeH2+4UaKqUw0zV5c1tajrcJ/1Ff6nhte4WuIXrilv1hJuf380gKz8/RHmcuqoPs3CT3vQmW8LLy1ln9wlyQrVxW953zz3hqT3mVk42FfYqIN3mteTBiR7u/Gy/akfE1Z2AwSWAAAAAAC0E61ujCXZSeFWG7jXmpixQlDrMac++omEGidi33PMuOjgmnRyVw/Go23NsRTnZpnw7pFTdvWsgtRWb6sl3Prdi1ZYxhpulKjqtFdeliNOS1eFqr0l3G91pglvbSFlfmPwbFe31XtqdzwZ+X1TroKM+ZjyZb7OVtPgHess0wbe3RBYAgAAAADQTrR6LicjmFSY5kXbva028HjsIajVOr6gsXW8qrHqT6dtF2Snf0bvoa7KwHga4gzptV6DVRmaSrARazq4xdp3ZozkdFNVXau00fupbM12fV78VFhmmYrF5OQPP9pHFWSy4k8Idw/10fbvQEYObeDdEIElAAAAAADtaGBxblJhmpsGj9runYhGb/YQ1Bos4w7eHv3kh2h7uMrOCEhhjneAudtA51CbopxM6Znrve3zi9aa+/0Y2DPP+zW4glwNFn1PDGqkA8LH9yuSf52xm+fAHTut0vRLj03b6a31JvUyyUNzVEr6DSy1KtNedelVYZk35BD30SY+lgGTfVRBSlonhLtDS23/HnpeOW3g3VD6/5MJAAAAAADwzR4waYykYdqMGNOr7SGlBo6xhvZ40ejNHoJ+sXabZ5Xgss1VMskWROZnZ8oBw3vLsx6TuwOuCTgn7jJAHp33Q8xjKKtxThmPRdeQ1OPwE+Rq+/qmysiUbT8GFueZtSATufiFRb73aR3bbUeNdbxvJVe90myyekvb5r0rLG0t4a7QU4fjlM27zbWXsASye0q4dmvjC8iQQFaBhGvLml5TRk7CQLFo14uk7BP7viMReGbhEKkvX+4RhyeeEA4oKiwBAAAAAGhH1XVNA1i275nbbMKzm7uVW3/8Ctv2EWt9x+G985tVWLrXTbSsKa92XN+wrVYq67wncyeSEQxE6/5e/2qD57Adr6rIHbeLPbjIy6oy5zHHstwVmHrR4zXTu2NUbO6yvbMCNZF/fb464XR493thAktbK7k70IwMx2k+wEYamoYGFe/5f1LgagFPFFiq3AF7eg7VGXTm11I67fGm50piQjigCCwBAAAAAGhH1fVNAV+8ITGJWrn9VAFaQ3diTRJXl04Z7ggsdWr3a0vWeYZmK7Y4w78VWxKHfLGcOHGAOcZYx67DdtyBoIZ7Hy7fktTz6FMkCgX9GlySF53e7RUy79S3MKn9battMGF0vOPLdgeWWc41LIOukxgZjuP+tIQlbAssg9mFEsjukVRgqZWb62adGHOoDutQoiUILAEAAAAA6CAVlrU+qiW1DTyVgS/asvz56jIThsVrJT9+woBmLdabq+p9rYD48crGFmOf7Pv55yc/SKy8Vo/da2r6xc8vlGTVNYQThoJqsGttUS+JVoL8IcUA1z3NPW5LeEZQXv6iKVCe8dqXjtcWGY7jdaRNt9Vu/kaCWQVJBZaxKjftQ3VYhxKpIrAEAAAAAKAd2Vu6axtCvtZ3THaYi0XzQA3r+hbmxNyHroH40Yr4VYvJtKG7WQWAZt1H++0JHuM1NX25q8LT7Vd7DW62LmTYVW0ay8yjd5ZE1pQ3VSm6aWj4wuK1kgqvcNbeOm8fXq5VrSf8Y170+sot1Y5ANjIcx7xq156a3sNtCx6QujJdc9J/YBmrctPvUB0gHgJLAAAAAAA6Skt4Q+LayRlTR/kO+mIGhuHYLeX9r3mtRYGkW1YwYCZm6xqPT5+xm1nv0Vr38Y6jx0a3i3U8yU5Nt3v1y/XS4FG2Gati004nkOvxxpr2HStEtcRru08k3n5Vpi2xfPXLdY7jcwey7tZsycj1rIys+eFd5y0Z2fGPwbNyk6E6SA8CSwAAAAAA2omGafaQUissw5qmJQjS/u+gEdHrO/TOl3P3Hur7OXX3a7fVmDDOa5jO+iQmbieiwdmYvoXRNR712PV3a91HbWdOJNZAG2sNyXi0+lDXBQ0kGTZarON96ozdoo/zG6LqFPZUxduvVk7W2j4z+ms4QSBrb80OmK2bV0Y2VDinwFetdAaYbs0rNxmqg/QhsAQAAAAAoJ3U2KorLfUJBu9oYPX3j1dGr08YUCT3/Od7389phXUaxm1XEL+KrqXiVTLq6zj7mQVxHz99535xp6bPPGps/Oe3XSYTNsaqtrRXh8YKUe2t217st47p6wxNtyvISrjfi19YlPB44wWykcpIL87P3aa3L5SN714R8zkYqoPWlNmqewcAAAAAoAvT0E1bf3WIja4tqe3aGm759fTnzQe/6OCdrBiVh/p8uj6h8zZnZVw87rCurNo5TCfd4gVnfqadj+9f5CtI1PZnDUZr6kOe+9O2dK301G1G9ekhM6aOjBsKxnquZN5br1Z0t5F9eshiWyXmn46fEPe49P1ftjn+IJ9EgaxWRrqne8dSNu82ye2/pwknvejtse4DWoIKSwAAAAAAUmCFhwtWl5s1H/XSz/Rp++N/9vinnrfHYoV8qbJXBoZCYdlWm1pgedLEAa7r/ZMOzvxMO8/Lykh4LPY283H9Cz3bv8f0K3S0oicbVqZip749PFZ4FCnIaXpNxXlZjvsLsuO/3njrYmrlp5/qTxMwBp3PG4996jfQVggsAQAAAABIgbtC0O/0affj3W5+65u46yImrtvzps/1W1tlYUVtgwkUvbZTWRmR3zQEmzqyj2Obd5ducly/ZMoIR/imD00UnPmZdp6blVxsYQ0kakn7d7p4HouIDCjSoTcRs1xTxHvkxG+E1ZA3lkdP2dV3IJvVa7TvcU1M/UZ7ILAEAAAAACAFXhWCfqZPx3u8+nZDZdLrInpu69pUn8teAVpe411dqdtdOmW41Nw8TUK3HmlCsB37FDi2WbW12nG9IDtTCm2VgxftPzxhcOYV6LlpWJqMVNaabC1ex6Ln1R46bqiodTymR3b8wDJWyDu0JC+p19h8YE5sWSWjfO8XSBcCSwAAAAAAUtC3MKfZbX6nT8cLn3QQzsSZcyT/ipfMpb1FPNa6iNZ+MgIBmdA/EtKN7de8PVr95OGPzX7/FaP1XF/D7CXrHbe9uMi5Tqb7KHrkZDjCtqLczJQCvePH90+6Jdxrv23d/u33WF5bsi7u9olawq2Q1+0nE5wt+om4B+ZIRlPVp1uxCTeBtkVgCQAAAADocjTkixX6pWv/XsNPkmk/jhU+/VBWHXNdTF0X0YvVjn3dYaOiIV2sCk69Tfd7/nMLPfflVSX6Q1lN3Nfy1tcbHO3MRblZKQV6kwYWO+7PzUw+sOzI4rV0+2kJ1/N1yZThjts0lP7DnG+T/oxraLn9qR/L0PPKJRBroYFgphSMmJ7UfoF0ILAEAAAAAHSLYTiXzVqcthAz1vqTybTmavh01uQh5nft9M60tXs71sWUpnUxNeT0Ul3XYC7/+P730dcVb43IeOtguqtEdX+JJl6f/vinUtV4DKowQfDmt8Iw2TUsO7q+PbJbVGGpZruqNJNdO9VLZomG7M1HBGX3GpPyPoGW6FrffAAAAABAt+c1DEfdOufblCd6u8WqXlxTXpOw0tN+23MLI63Wp+460LPF3Dr+xWvLoyHn1R4VnFX1oejaktbriq4RmeRrc1eJxptMbWcdo/v3ZHyxzvm4eSu3SpfitVCnzd73vJfwM+lVpZnM2qn+1rSMfINoB0d7IbAEAAAAAHQpscJEacFEb7dY1Yv20DFWpaf9Nivg3FhZK9kZ/v6JvueQkpj32V+XtUbkaJ9ralrcQ2p0Mrkf9iJMDYe1ojUZer7ue3+Z47brX/8q7e387WmtK9B2W+gjSPf67CWzdqqfNS31snTak7SDo90QWAIAAAAAupR4rdDpqkqLtf6krmuZc9ksCV7yohluY57Hej77c7se99qS9VJT39RS7VYXCkcDwLqGSDWln9eloeW/z/6R+KVt6eEWTCa309AymbDRq83e3g7fHT6bfoJ0r+nqyayd6mdNS71k7Uq0JwJLAAAAAECXEitM9JJqVZoGgYOL82KGi8rvMaj6UFhWJRhsYwWAtQkCS3e13esJJlO7j8Nd4Zdo/cp4kgkbvSpj9XpLWp07GnfYmEqQ7jVd3V0VC3R2BJYAAAAAgC41+VsDnZt+PNrXPltSlbZ2W/yAsTVoAFjXED9AdFfb6QRpL7EKJ90VfrEmk/uRTNjo2ercglC5I3KHjVkeb4Kf9m73dHXCSnQ1BJYAAAAAgA4v1nqQsULLvYY2rfOYneGdzOnN185ekvLU8B165Utb0wAwXoWlvlJ3td1XG5oPaVGxCifdFX7WZHJ7C7L1XPEkGzZ6Vcbq9akj+0hXYoWNj5yya7Qa1y4d7d1AZ0dgCQAAAADo8JWUXpO/4631p6GmpUETIA9aqPh5C6aG/7/JQ5J8ZZEw8ewfJf84ewAYr8Jy5/6Fzart+vXITu55XBV+Xi3Il04ZHre12Xqvkgne9Hku2n9Ys/1ohWhXGrwTb81ONbQkj4pJdHuZ3f4MAAAAAAA6XCWlFXhZQaK2zoaTWOuvuq4psBzYM88Mw4nH2rc1XduPPQc7p3XrMXpVzNlpRefkob0kWfYA0Jos7uVqj4Cw0nYuYu6/cXBLrAEuek7c50Wnlev50vdgVJ8eMnVUH5m9ZH30+oypI5MO3t74akPcqefdYZp9vPcX6C4ILAEAAACgjViVghpU6Hp92gLb1UKYlopVSamTqnUgjDvg6VuY47mfqrqmidvTxvSVe//zva/nX7y23Pf7uMi17bDe+fJ1jBDKogGsVnUma+d+hXLNoaNMAHjXu9/F3tBV8qjHur6iNu6+t8vPlu175iYdNHqFmDdPkxb5Yu22tE5z78j0zwD9PISTXL8S6A5oCQcAAACADrgGY3flOSk6HJlU7RUEauWk1zm0t4RrCHfQjtv5en4NRuO5bNZi875p6OheSlKPPScz/j+zTQDrcXui9SDrbK+/Nk5LuLtFXoPVRHRNzN9OHdnuA1z0ffSqUO1qg3diTQyPVd0KdEcElgAAAADQBpJdg7Gr0IBP16IMXvKiudTriarO3PQ8jelXKIU5GZ73eZ3DaluF5a+fWyhvfeNsNY5Fg9F4gdqtMSZuWxJ0hBtemyR62JfrtkVa4y+bJbe9HfsY3JWIGqImUlZT3yHC81jharJrYXYWXmuDugcmAd0VLeEAAAAA0I6Vg+lode2oreYaTtoDPq16tK7fMm2M52P02DU8c5+nhavLzJAc8XkOn/psVdJBotJgNBY/1Yp1cSZ4x2MPsxMFqvHWOHRXInq1HcfS3utExgpXdW3QrhriebXVA6DCEgAAAADahAZH7rZfv+vVeU3N7gyt5ve8tzSp25WGNweOcLZv63mL0wXteQ7fXbpJUhGvks9rfUU3n7mo5+MStYV7CSQ4fnfbcUvX72yP70i8EBlA10RLOAAAAAC0ASs4clcHTh3ZJ+7jEgWS6Wg1jxeItoR9HUk/t1uyMgJJhYBeIaMO6EnGgKLchO24ida3bKncrOT+ia5bb1eQHb2ekxFsdq7sbceJjr61X18irOkIwEJgCQAAAABtQIOjX+452HGbxkN/mPNt3IDQakO2B5LKCiS16q8lreatWaGp6/Ilc7t1PK8tWe/7OYaW5HmGjK7MM6GzfjQkYdtxvPUt06GqLrl28pysoGMCeE1DyPO908+eDtN56ozd2vX1JcKajgAsBJYAAAAA0EZeXLzWcd1PNWSsNmRt303HVOXWHAZ07j7DPG//dYzbreNJxsyjxnrePn5AUVL72VpVn3Cbnfq2fFL1zv3SN+26pj7kWTV58fOL4gaCuiakl47Qem2Fq+09sRxA+yKwBAAAAIA0SbTWpNewlETVkLHadPX2dExVbs1hQDpYZ7Rt6rdWPV42Zbj8PsbAHet4/Dp5lwExA63dBhUndaxbq+t8tSy31Ji+iVuz/dKs2qsmctmWqpgVshoIPnbaJPO7ta6lddkVJ3ED6JwILAEAAAAgDazW6s8bW6s/91hrMpZ41ZBeFZRW+268cC/sM1zVKj1JcRiQ+HiOlVuro9d/NLRX3LDSGrzi12PzV5lwWKeRu5/XPSU8ka1ViQNLDftKezStGZmMo8f2NZdPfrYq5cE8bplx1pyMVyFL6zWAji6zvQ8AAAAAALqCi59fGOP2RSYgihcuxqps0+At1rqC2r4bDodNMBorsNLnjbVfDVPtreBew4CG3fC6LN8SCRwHl+SZ9utY+4z1HO7J3Rouzl6yzpwPDSe1atG+T73uflw8Gg7fOufbaEWn1/P68a8Fq83r1bR2bXmNObapo0rlqU9/cJyDjbY1I5Mxd/lmSbd9h/WSt77d6HlfogpZPed+30sAaGsElgAAAADgk4ZhWilphW0aaFnhW6zJ18u3VJlL3d4rXIw1NCZRVaaGnBo2xgrn7IGV+7i3VtfHDCvVpVOGm2FAdss2V5nn0jUQ/QRd7rUxLRouWrdbA37c+9SZPNbpzM4ISG1D4prEe95bagLLWM9riXWf5sLLGoNJpe+V+/3Sc5CqteXxg84J/Ytk6qg+8uSnq6KfGQ1IT5gwoNl7YTl2fH/5blNls+NKV4UsAHTLlvB33nlHjjzySBkwYIAEAgF57rnnHPfrfy2cMWOG9O/fX/Ly8uTggw+Wr7/+2rHNpk2b5JRTTpGioiIpLi6WM888U7Ztc/6XpM8//1z23Xdfyc3NlUGDBsktt9zSJq8PAAAAQNehlYHulm8N36zp2qmuf6jhmdealypWVaYOTYk3jMQ+dMdrCrgGXPEiwNeWrIt5n99hPF5rY1rcE89P/sc8cw60wlGP1X46/YSVynoP4j2vnpfte+ZKR6Lh4oQBRWbAzM3TxsjSqw6WhluPND9Lf3Owua0417vWKDsjGB06ZF+PUitkWY8SQGfWroFlRUWFTJgwQe69917P+zVYvOuuu+T++++XDz/8UAoKCuTQQw+V6uqm/+qlYeWiRYvk9ddfl1mzZpkQ9Fe/+lX0/rKyMpk6daoMGTJE5s2bJ3/4wx/kmmuukQceeKBNXiMAAACA9h98E28Yjt99Wm3HbonitCEleeZSKwgnD2k+CGb55qpokGhf81JpNWQgzjRnP0N3vKaAJxKvfd3vMJ5Yxx5rnU49B/YKx2TlallmgufdZfsix5qaHYGfcFELfLxkZQRZjxJAlxQIaxljB6B/AD/77LMyffp0c10PSysvL774YrnkkkvMbVu3bpW+ffvKQw89JCeddJJ88cUXMmbMGPnoo49kt912M9u8+uqrcvjhh8vKlSvN4++77z75zW9+I2vWrJHs7MjiyFdccYWp5vzyyy99HZuGnj179jTPr5WcAAAAADom99qM9qDO3Qo8JIk1GTXkjLVWZCL/OmO3aDXkoQ98IK9/tSF6n/uYNJca3y9SbWd/PV771Mf95OGPPQNIrcCsuWWa+V1DWj8VoHZ9CrJlfYy1Gk014EWR44sn1bUkU2VNH4/3vDqjRv8F3CH+Edz4/ms7fLxqWZV7+SzPStPz9x0mtx+9cyseIQCkTzL5WoedEr506VITMmobuEVf1J577ikffPCBua6X2gZuhZVKtw8Gg6Yi09pmv/32i4aVSqs0lyxZIps3ey96XFNTY06i/QcAAABAxxevmtAd91hrMsartrQqM1MNK93rU26tqnfc7z4mDdPsFYzWNGe7Cf0L5YNlm82xxwrerApM1bcwJ+njjhVWKr+txnrs9xzT+mFaRqAprLSfM68B2qFWCCsDjQFxKsYPKEoYVupnMFZb/J3vLm02IR0AuoIOG1hqWKm0otJOr1v36WVpaanj/szMTOnVq5djG6992J/D7aabbjLhqPWj614CAAAA6PjirV/oRSsaY63JaF/7MVXW+oKWLdV1CY/HPSzlyDHOf8/U2KZix6ITvq0W+FVpbIFOtHam2+ShvaS1HTW2XzSstBw9tp8JJ5OVTOxodWlrOPrYaZNihqnaqq6XqYa/8QYvKf0sJLvEAQB0dEwJ93DllVfKRRddFL2uFZaElgAAAEDrc0+z1kE1flq2LfoYDRj9ZlXuika7RNOmEzl11+0d4Z6+tm83RtaG9NqvuS0ssqWqzgSN1us/eMftHNt9n2BStbZzx5oq3RIBV+WmH2UJAtqWHIt1/p5buMaEs/aJ7Tv0zk9pv9mZQRMIJ6IFleP6FcmMqSOj77EGlxp+6+dpVJ8ejvvUXz9cJr986nPHfq6dvcS8jnif8XjriVr0eZP5ngBAR9dhKyz79etnLteuXeu4Xa9b9+nlunXO6XX19fVmcrh9G6992J/DLScnx/TS238AAAAAtC6vadZeLdvxBuhowJdswOiuaLSeI5ng08uw3gWO/elraWjMwrz2G7a1qltTyPUxV770hWO7ROtRbq6K3c7dEvZBPn6V1zSYy+G986NDcVLsnjayMgKmynNwcZ7juNwT2xev9TcYyM1PWKlK8rLkt65AUgNDXXu08vdHmEt3JepJE7dvtp9Yn/Fkhxf5HYQEAJ1Fhw0shw0bZgLFN99801HpqGtTTp482VzXyy1btpjp35Z///vfEgqFzFqX1jY6Obyurum/7OlE8VGjRklJSUmbviYAAAAAya0/6W7ZThRqamh0yf47JL3OpJ31HC1d67CqLhLW2V9bKu77YFlS2yc5X8c3rfTUikA/k9atUPm4hz4y1/OzM0zVofLbqp2dEXSEm8eM6yc1N08zw4R65mV6ns9Eu25BVuqwsbIuYdDopufAzesz7uYnhPcK3QGgM2vXlvBt27bJN9984xi08+mnn5o1KAcPHiwXXHCB3HDDDbLjjjuaAPO3v/2tmfxtTRLfaaed5LDDDpNf/vKXcv/995tQ8txzzzUTxHU79dOf/lSuvfZaOfPMM+Xyyy+XhQsXyp133im33357u71uAAAAAP7Wn3S3bMcLNa2W2Mc/XZXU6X1+0VoTPFmPb2kruKWytiHltTU7oje+bppublV/HjW2r3ywdJOsr4wUiOhajRo0VrlS01TWAa0PhWT7nrmyYktkDc7dBxW3+Hxqy/dho/qY97yl3J+7xNsHkl6WwD5ESJ9rweoyCcVYsxQAupJ2rbD8+OOPZZdddjE/SteN1N9nzJhhrl922WVy3nnnya9+9SvZfffdTcD56quvSm5ubnQfjz76qIwePVoOOuggOfzww2WfffaRBx54IHq/Ds2ZPXu2CUMnTZokF198sdm/7hMAAABAx+E1zdo9hCZRqKnB48oUhszYK9zSFS5W2ios/bT1ShtVB6bTC4vWRsNKpcOs3WFlqvR9tb8RRTlZLT6ftfWhtISV1vEl24rtNU3ca9CSm9VuvnN/7zVEZy9Zn9RxAEBH164VllOmTJGw+Vso9n+Buu6668xPLFqN+c9//jPu84wfP17efffdFh0rAAAAgNajQaOu3eim/1ywJl7HGz5iBT6JJirHYg8806XaFlhqW69WJLZEZ6/QjEUzPK82cb1phS18LsrNbPH5DLdByB6L12dLw0r9jPtdGzTWd4A1LAF0NR12DUsAAAAA3UesNR6LcjLNxOvPG9esjDVwxmqJ9TNR2S3QGHhaa1cmGmqTSoWlVsj930Ej0rLfriZODYvDb1/90rlW6ZTh0t78Vnlan606VzKrw4P+dcZuzQb0xOJVWeqnQhMAOhsCSwAAAADtLlYbdllNva/HWy2xGugkw1qrUgPPUx/9RNLp+02Vjmnm9jUtkXzVo1bg2gfdPPXpDy06jTGWlEzKmvKalAN5vV6cm+U7rLQP4LGOPdkKTQDoLAgsAQAAALS7lq7xaLXETh1VmtTjsjICcvTYvqaKM12VlYU5kdZlrQq1KkP18o53l3bo9Sg7i4tfWGQulzcO4/HDHvCpS6cMl/H9ijzXlEyG38pGz7VXU2jltgbw6LHnZgbNZTIVmgDQWbTrGpYAAAAAkI41Hq2W7lvnfJvU42obwmkbwmIpT1AVWpCdYX7WbatN6/N2F8s91jqNZ0hxnhTnZZlwcFSfHjJj6kgT8N08LXL/ZbMWJ/25sfitbNRAXielhz2WIkiWhpZ+J5MDQGdFhSUAAACAdmdVjmWmWPG2papOftLCoTZtpaK2Ie1h5YQBReb8FdsG03R1g0vyfG23dluNmbBd+fsjzKW7GvGWaWNSWg/zsinDfVc2Rlu5bbfpdVq5AcAbgSUAAACADhNahv1OYPFY37CrTtH2Q4MvPX/77NA7pcen2hjdIztDWsuAIu8J3EMag8qZR41N2yRvDS018J3QP9JqrVWZ+jz6u96mLeTWfXqpbdi/nzYm6UB+YM/c6G23HTmWVm4AiKH7/Oc3AAAAAO1KW7Z1+Iiu56ctslp1Zm9t/ddnq6QhydQxOyNg2rq7M12HUSv99PzOWpxae/v4/kWmZbqmPpRU8LstjYOEtLjWPkQ7GGMqjhVUWiHgzx6bH/c4NMzWc5OojTpRq7XVQp4q3fcnK7fI7978xlx/4MNlMrhXHu3dAOCBCksAAAAAzWjAY59wbU1mTvUx+ruuUbmgcQiNXtonPuvlT/4xL+l3oruHlZrpjelXaH6/+PmFKe/nt1NHmpbpcf0j+2oPO/crclz/YWtkqI690tE9YEZDwINH9kl4jq6f/ZW0N/2MW2GlWrJum+M7AABoQmAJAAAAwMEKF+0TrhMFK4keo5WVWi9nxYvW5cXPL3Lc3xrcE6J1KngqVYxWK3JHoa9HO+itdRCTmZrtZgV6WvUaTypTtfW8aUt1Ip+vLnNcN2s+BkSKc7Nirj+pn6/nFq6Ju189R8lO424N7s94uAOFqQDQ0dASDgAAAMAhVqWehotWy6y7vXt1WY3nY07+xzzJCAZithov2xJp19X9pLtWUgfR/PaQkSYQsk+Ivnb2kqT39fhpk0xYNuzGN0yLcXvSakNln3jdUlagp+9vn4JsWV/RfCjQ0JI8KcrNbDbtOp6MgMjS3xxsft9zSEn0vVAabCeSKGy8+IVI4B2PhoKpTONON6/PeEcJUwGgoyGwBAAAALoxr3UlY1XqLd9S5aimtGg1ZSx1obD5iUdDLH3uZIIwP7Ty8BiPdQlPefSTpPajQZ0VCur6ifbX3hJaebi2vMYEj1NH9ZHZS9b7Wkfy0VN29QwpdWp2KmGqO9C77/jxnq9RX7ueO7/vkVYT7ty/yHONSF02wK94YePyBK/XXYXanrw+4x0lTAWAjoaWcAAAAKCbumzWYs827kSBlAac6aQhnQal6a6wDMcJjuKx2natFnL7NGpr0It9YnSyreJawahrMWrlodXqfPO0MeYy0TqS08f2jVlR6XdqdqJAz+s1WmtHJjp3jv02hsZe/O5HpRo26rGP79d83cv2Yn3G7UsUdJQwFQA6GiosAQAAkNZJz+g87+Otc75N6jFWMKfvfTpZFWZFOZlSVlOftv2e+ugn8sgpuzb7fOpn1quCUIPEn+0+KFrpGKvl2j1N2qo4tQKoWPwGZ7GOT8PKZ36+R8zHWUGjvQV+4dpyafCocNXMLCcz6Ps1Jjq2ZNvVp44qjVuZ61Xd6mVwca4s86gI1sd919iK3lF4vT/paukHgK4mEA7H+ysVqqysTHr27Clbt26VoiLn5DoAAIDuJBrMWAMjGi/1H+GElm1bGXnPe0tNVaQGROfuM0xumTYmqX3oFG8/gZFXC7Pf9Qf9yssMSlUa9+fm9fnUz3I6gyNrfzo4xusfWMkGaOk6Pn2fvdqQx/cvkvkX7S+pyLr0RYk1nN1vKJvo82eFv4n2516eINnjAAB0zHyNwDLNJxQAAKAr8ww/pDH8uDi18KO70qBFh9tY60Xq+oPa0pso+NWw0qsy8pIpw5MKLXUNwXSGjm1BKwyXbqqKhnixwkFxh3P92u7z6a629Bu8dabjifXZ0QniNbdMa9E+LNqG7jekTXf4DABo/3yNlnAAAAD49sXabc2n3IrI4rXJVep193Z4r9BRh6VosJSoWvXOd77zvF33N3vJOl/HpK/Dq024I9IKUq8QKlZlnbTzFOaO1vbbGseTjs+Ofn9iVVjqdPdkqj9jta8DADovAksAAIBuvA6k13GoWMeWEQwknPjcVc+tux1eK039BIzuikqv9fbsNFhyr49ovZ7C7Iy4598amhOv2tJv0NdRwkodQuNFz6Uf7TGFuaMFaOk+np369vCstB7TL/awoGTWwmQIDQCAlnAfaAkHAABtvQ5kqu3CyQR48YKrWMeWc9msmIFZR1jHMtZrSrZd2mu/OsDF3cKaqN3YOvdameo36M0IiIztV2jer749sk3Aab0PyYj1fgy78Q1TzdkZxGsxzrjkxcTt4I3njfUMO2abeeTPuUWyfEtV9M+5244aSzs3AHRRrGHZjicUAAAglXUg1ZDiPFl61cFxg8RkQ0F367E9gNQgzc/QFXsoFy/smtAB1rEcdsPrMSsYUw1UE1UkxqoCdAfTyUjlMV77GNe/sFmFqZ+gr6OI1xrs93VcOmW43NyCsBreWDcSAJAs1rAEAADowLRyzitoWbalKlqR57ddOB7dl3udROt5tapp7bbItGe/awDq/uJV5n22usxUYGrbuK5xp22jybZjt7Sd26pI9XLyP+bJY6dNSjq0vPiFRXHvL8zxXmVJX0eqwWM6AsWwrUVc9SnIlvuOHy+dSbzWYK3GS1QpqmH77CXr5WZ/c2DQidveAQBdS7C9DwAAAKC70SAuXiCpYV0syQwPiRd8ajgaK2jz0rcwJxrAxaNtz9o2rZdWWKYhpB9WRaI+TvdhPV6rRO3baIWqThjWS7/7to4t1vHE2m+ikFatr6g127n3schjQFF70uPU15/M+95SgcbKW20V1rZ8rUb1Q7dL1F6sSyR0tIE7AAAgPVjD0gdawgEAQEvZ16QMJ1izTysTY7VqDynJk565mb4qEDU4c6+5mCqtzttQUZtSANcnP1vWXndowu36Xv2aCdVinZcBRTmO9Rzt7e3Kb4u71XrvZ01Rv/vUdScbOlI62UHECh31nP/k4Y9jfp7iDdtJZj1Os5xB/+QmTgMAgPbP16iwBAAAaGVaIaiBmIZtYR9VgFNHlca8X8MZdwWitmF7VRvGq+RMlgaJqeZx6ytrZfqD/427jR57rLDSOi/W2pTWcVjhora3W5WZflit9+6Wb/t+VTL77AphZbr/YXDZlOExKyQ1ZM8Mxq7X9TvV26qy1GDSzRoEw8RpAAA6HyosfaDCEgCA7qclaynaH2tNefZLcxetCPvt1JFxK9DiVUKW19SbY9bg072GZXuKN6lbA1e/4aCXZNeKtFqTk31/uiqrorElE8T1PcjJDMqoPrp26ciEk57jvefJTJu2D3/p2yPHHMja8hrfxwEAANoGU8Lb8YQCAIDO05ptDe7QKi17GBlrKrR9aEmsMDPRRGm/xvcvbFGA11FpS7uGSVagOnvJOnMea+pDHWq9x7ain6l4laVtwYTkjdO4o+3xjdWJydC2/Zpb/E+3ifVd0crM3zPVGwCALofAsh1PKAAA6LjihYm6XqEVOvqp9vNa71Af35IKNXQvVsAXvOTF9j4UR0WjvWIxmTVQJzSGnsmwPxcVkQAAdG1lSeRrbTciEAAAoJ1buONNzdbQxNo+3pRui3u9w5P/MU8ygoG0DblB16efFzWkODfltvTpY/vK0k1VsnBNWYvW0bS3Tev3wPou+BncZIX2qawVaX8uAAAAC4ElAADocpWT1jAaXTNR3fPe0oShi1Z4WTTwTLYdW4fC6A/gV0Pj52Xm0TsntYxAoHEpg9uOGhsNGluyBmjs0Tci5+4zzHMdVCsopTISAAC0BgJLAADQrgNq0iFW5WQyA2cKczJN6KOvIV6Ag86zNmNHN6ZfobnU74qG634+r/rZbLj1yGa3+6kKjreuaCzWkCQr9NfhPL/eZxhrTAIAgFZFYAkAQDfSGsFirOpG+5qQqQ6/8WvR2qbqyFRpuEbAlh4aaulwonQMH+rK7C3UGgzuNaQkpbUjE1UFJwqP9XsXjx5brOnuAAAArSEQDic7/6/7YegOAHSdSrzu7LJZiz0ruLSyqyVhRN+rX/MMQ7Rqa+lvDo4ZVMZas08HkWhrtYZe2o4a69gS7Qf+WWsQpos15TnWZ66z0snZ4/sXySEj+7T4dSWahD3shtc9P9tDS/Lkuxjfq1gTt/cYUhIzPE52sjcAAECqmBKeZgSWAJAesf5B3dLArKtKR7hr7eOLtdvirq+YqBoy3v7jVdGN719ojlulGi4W5WTK306aaI7P7+uBfxqAFeVmJr3+YVZGQC7cdwcJxWkX1hb7BavL0xqGtnd7ujVN25pu/dnqMt+P1XBwTF/9Tox0DLlJ5rtln+adzMTt6Q/+V15YtDbp4BQAACBdCCzTjMASQFeUSjtuSwO0eEMhUg3M0n2M6eA+hqmjSuWpT3+Ie67djxnaK98zXEgU7tr307dHdlIBoTXI4ycTBsjsJetinkP7c9Q1hFo0mRgtp+/bdi0I5DQA07cwmfbtWFV+bn4mTMcKQ48YXSrPeXwHkpWowtAvDWMfPWXXZmFhzmWzfIfnyf45Fy+ATIVWvLIWJQAAaC8Elu14QgGgM4hXFRfrH9SxHnPU2L7y3M/38PW88cKLIcV5svSqg1sUOsaqIIoXErj/Aa8tyLqOXDLPbw9/k8nutGV6bXlN0sGi0mOdOqqPfL+pMmHImQ7WOUxUUdmVBQMiHa2o015tZw+3dPq0O0SzAuni3CzPACx4yYspPW88yUyu9qr0S6WKUV9nTmaw2esbduMbsmxzlaQq1mtOpop0Qv8imX/x/ikfAwAAQGdGYNm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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "model = ExponentialSmoothing(trend=\"add\", seasonal=\"add\", sp=7)\n",
         "model.fit(y_train)\n",
@@ -104,9 +491,7 @@
         "    y_pred,\n",
         "    labels=[\"Treino\", \"Teste\", \"Previsão Exponential Smoothing\"],\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -125,7 +510,30 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 6,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 6,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from sktime.forecasting.auto_reg import AutoREG\n",
         "from sktime.utils.plotting import plot_series\n",
@@ -140,9 +548,7 @@
         "    y_pred,\n",
         "    labels=[\"Treino\", \"Teste\", \"Previsão AR\"],\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -159,15 +565,347 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 7,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-dd737016-300d-4d25-b4dc-db19ebfe53d2 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-dd737016-300d-4d25-b4dc-db19ebfe53d2' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>STLTransformer(sp=365)</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('82d9f752-0201-49c7-a640-b0413556cc00') type=\"checkbox\" checked><label for=UUID('82d9f752-0201-49c7-a640-b0413556cc00') class='sk-toggleable__label sk-toggleable__label-arrow'>STLTransformer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.detrend.STLTransformer.html\">?<span>Documentation for STLTransformer</span></a></label><div class=\"sk-toggleable__content\"><pre>STLTransformer(sp=365)</pre></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "STLTransformer(sp=365)"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.transformations.series.detrend import STLTransformer\n",
         "\n",
         "stl = STLTransformer(sp=365)\n",
         "stl.fit(y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -178,7 +916,28 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 8,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/var/folders/_2/9y4tsvdd2n3gqjgd2zmlr1km0000gn/T/ipykernel_35866/1542615419.py:8: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
+            "  fig.show()\n"
+          ]
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1000x800 with 3 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "fig, ax = plt.subplots(3, 1, figsize=(10, 8), sharex=True)\n",
         "stl.trend_.plot.line(ax=ax[0])\n",
@@ -188,9 +947,7 @@
         "stl.resid_.plot.line(ax=ax[2])\n",
         "ax[2].set_title(\"Resíduos\")\n",
         "fig.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -201,7 +958,30 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 9,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from sktime.forecasting.trend import STLForecaster\n",
         "from sktime.forecasting.naive import NaiveForecaster\n",
@@ -222,9 +1002,7 @@
         "    y_pred,\n",
         "    labels=[\"Treino\", \"Teste\", \"Previsão STL + AR\"],\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -235,7 +1013,358 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 10,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-6fef2bbb-4834-4121-8dff-6d0bb66fd3b4' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>STLForecaster(forecaster_resid=STLForecaster(forecaster_resid=AutoREG(lags=31),\n",
+              "                                             forecaster_seasonal=NaiveForecaster(sp=365),\n",
+              "                                             forecaster_trend=AutoREG(lags=31),\n",
+              "                                             sp=365),\n",
+              "              forecaster_seasonal=NaiveForecaster(sp=7),\n",
+              "              forecaster_trend=AutoREG(lags=31), sp=7)</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('dc55c9a6-b9f9-4cf8-a518-b3eea3a894a4') type=\"checkbox\" ><label for=UUID('dc55c9a6-b9f9-4cf8-a518-b3eea3a894a4') class='sk-toggleable__label sk-toggleable__label-arrow'>STLForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.trend.STLForecaster.html\">?<span>Documentation for STLForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>STLForecaster(forecaster_resid=STLForecaster(forecaster_resid=AutoREG(lags=31),\n",
+              "                                             forecaster_seasonal=NaiveForecaster(sp=365),\n",
+              "                                             forecaster_trend=AutoREG(lags=31),\n",
+              "                                             sp=365),\n",
+              "              forecaster_seasonal=NaiveForecaster(sp=7),\n",
+              "              forecaster_trend=AutoREG(lags=31), sp=7)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('06ef09bf-b7af-415f-8fb2-e1f25570d4db') type=\"checkbox\" ><label for=UUID('06ef09bf-b7af-415f-8fb2-e1f25570d4db') class='sk-toggleable__label sk-toggleable__label-arrow'>forecaster_resid: STLForecaster</label><div class=\"sk-toggleable__content\"><pre>STLForecaster(forecaster_resid=AutoREG(lags=31),\n",
+              "              forecaster_seasonal=NaiveForecaster(sp=365),\n",
+              "              forecaster_trend=AutoREG(lags=31), sp=365)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('f3914c9e-7c0a-439e-a3c6-5407f6aab77c') type=\"checkbox\" ><label for=UUID('f3914c9e-7c0a-439e-a3c6-5407f6aab77c') class='sk-toggleable__label sk-toggleable__label-arrow'>forecaster_resid: AutoREG</label><div class=\"sk-toggleable__content\"><pre>AutoREG(lags=31)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('9fcaf8cf-2e66-4f39-ac9f-7679b4af86c6') type=\"checkbox\" ><label for=UUID('9fcaf8cf-2e66-4f39-ac9f-7679b4af86c6') class='sk-toggleable__label sk-toggleable__label-arrow'>AutoREG<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.auto_reg.AutoREG.html\">?<span>Documentation for AutoREG</span></a></label><div class=\"sk-toggleable__content\"><pre>AutoREG(lags=31)</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('4d913875-b8e0-49db-8e1e-b76adce6d3d5') type=\"checkbox\" ><label for=UUID('4d913875-b8e0-49db-8e1e-b76adce6d3d5') class='sk-toggleable__label sk-toggleable__label-arrow'>forecaster_seasonal: NaiveForecaster</label><div class=\"sk-toggleable__content\"><pre>NaiveForecaster(sp=365)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('68bdb931-1797-406e-8533-601b994ce59c') type=\"checkbox\" ><label for=UUID('68bdb931-1797-406e-8533-601b994ce59c') class='sk-toggleable__label sk-toggleable__label-arrow'>NaiveForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.naive.NaiveForecaster.html\">?<span>Documentation for NaiveForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>NaiveForecaster(sp=365)</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('30cb9b59-2c8b-4b36-b372-c0b9492eee7e') type=\"checkbox\" ><label for=UUID('30cb9b59-2c8b-4b36-b372-c0b9492eee7e') class='sk-toggleable__label sk-toggleable__label-arrow'>forecaster_trend: AutoREG</label><div class=\"sk-toggleable__content\"><pre>AutoREG(lags=31)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('b85bab9f-39b9-48a7-b82a-c61d697a7a2e') type=\"checkbox\" ><label for=UUID('b85bab9f-39b9-48a7-b82a-c61d697a7a2e') class='sk-toggleable__label sk-toggleable__label-arrow'>AutoREG<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.auto_reg.AutoREG.html\">?<span>Documentation for AutoREG</span></a></label><div class=\"sk-toggleable__content\"><pre>AutoREG(lags=31)</pre></div></div></div></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('fdb90295-2932-405a-8b33-c8599a07ed89') type=\"checkbox\" ><label for=UUID('fdb90295-2932-405a-8b33-c8599a07ed89') class='sk-toggleable__label sk-toggleable__label-arrow'>forecaster_seasonal: NaiveForecaster</label><div class=\"sk-toggleable__content\"><pre>NaiveForecaster(sp=7)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('da0f01db-e1ee-4a25-8dbf-db7af5bce660') type=\"checkbox\" ><label for=UUID('da0f01db-e1ee-4a25-8dbf-db7af5bce660') class='sk-toggleable__label sk-toggleable__label-arrow'>NaiveForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.naive.NaiveForecaster.html\">?<span>Documentation for NaiveForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>NaiveForecaster(sp=7)</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('dab4e653-7c42-45de-ba36-a21032a9362b') type=\"checkbox\" ><label for=UUID('dab4e653-7c42-45de-ba36-a21032a9362b') class='sk-toggleable__label sk-toggleable__label-arrow'>forecaster_trend: AutoREG</label><div class=\"sk-toggleable__content\"><pre>AutoREG(lags=31)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('cb8eed40-5f9d-43e5-bd54-a836ddd50a15') type=\"checkbox\" ><label for=UUID('cb8eed40-5f9d-43e5-bd54-a836ddd50a15') class='sk-toggleable__label sk-toggleable__label-arrow'>AutoREG<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.auto_reg.AutoREG.html\">?<span>Documentation for AutoREG</span></a></label><div class=\"sk-toggleable__content\"><pre>AutoREG(lags=31)</pre></div></div></div></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "STLForecaster(forecaster_resid=STLForecaster(forecaster_resid=AutoREG(lags=31),\n",
+              "                                             forecaster_seasonal=NaiveForecaster(sp=365),\n",
+              "                                             forecaster_trend=AutoREG(lags=31),\n",
+              "                                             sp=365),\n",
+              "              forecaster_seasonal=NaiveForecaster(sp=7),\n",
+              "              forecaster_trend=AutoREG(lags=31), sp=7)"
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "model = STLForecaster(\n",
         "    forecaster_trend=AutoREG(lags=31),\n",
@@ -250,13 +1379,34 @@
         ")\n",
         "\n",
         "model.fit(y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 11,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 11,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_pred = model.predict(fh=y_test.index)\n",
         "\n",
@@ -266,19 +1416,28 @@
         "    y_pred,\n",
         "    labels=[\"Treino\", \"Teste\", \"Previsão STL + AR\"],\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     }
   ],
   "metadata": {
     "kernelspec": {
-      "name": "python3",
+      "display_name": "tsbook-py3.11",
       "language": "python",
-      "display_name": "Python 3 (ipykernel)",
-      "path": "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/share/jupyter/kernels/python3"
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.11"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 4
-}
\ No newline at end of file
+}
diff --git a/notebooks/part1/04_metricas.ipynb b/notebooks/part1/04_metricas.ipynb
index 118379f..63b7598 100644
--- a/notebooks/part1/04_metricas.ipynb
+++ b/notebooks/part1/04_metricas.ipynb
@@ -17,7 +17,9 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 1,
       "metadata": {},
+      "outputs": [],
       "source": [
         "import matplotlib.pyplot as plt\n",
         "from tsbook.datasets.retail import SyntheticRetail\n",
@@ -31,9 +33,7 @@
         "model = NaiveForecaster(strategy=\"last\")\n",
         "model.fit(y_train)\n",
         "y_pred = model.predict(fh=y_test.index)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -51,15 +51,26 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 2,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "np.float64(615.0555555555555)"
+            ]
+          },
+          "execution_count": 2,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.performance_metrics.forecasting import MeanAbsoluteError\n",
         "\n",
         "metric = MeanAbsoluteError()\n",
         "metric(y_true=y_test, y_pred=y_pred)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -74,15 +85,26 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 3,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "np.float64(633773.8777777777)"
+            ]
+          },
+          "execution_count": 3,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.performance_metrics.forecasting import MeanSquaredError\n",
         "\n",
         "metric = MeanSquaredError()\n",
         "metric(y_true=y_test, y_pred=y_pred)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -101,15 +123,26 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 4,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "np.float64(0.21292470853237802)"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.performance_metrics.forecasting import MeanAbsolutePercentageError\n",
         "\n",
         "metric = MeanAbsolutePercentageError()\n",
         "metric(y_true=y_test, y_pred=y_pred)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -120,13 +153,24 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 5,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "np.float64(0.22359840490570626)"
+            ]
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "metric = MeanAbsolutePercentageError(symmetric=True)\n",
         "metric(y_true=y_test, y_pred=y_pred)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -156,15 +200,26 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 6,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "np.float64(10.127736897882464)"
+            ]
+          },
+          "execution_count": 6,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.performance_metrics.forecasting import MeanAbsoluteScaledError\n",
         "\n",
         "metric = MeanAbsoluteScaledError()\n",
         "metric(y_true=y_test, y_pred=y_pred, y_train=y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -179,15 +234,26 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 7,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "np.float64(57.09087480132447)"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.performance_metrics.forecasting import MeanSquaredScaledError\n",
         "\n",
         "metric = MeanSquaredScaledError()\n",
         "metric(y_true=y_test, y_pred=y_pred, y_train=y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -210,7 +276,20 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 8,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from sktime.utils.plotting import plot_windows\n",
         "\n",
@@ -221,9 +300,7 @@
         ")\n",
         "plot_windows(cv=sliding_window_cv, y=y_train)\n",
         "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -234,7 +311,20 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 9,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from sktime.split import ExpandingWindowSplitter\n",
         "\n",
@@ -245,9 +335,7 @@
         ")\n",
         "plot_windows(cv=expanding_window_cv, y=y_train)\n",
         "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -267,7 +355,195 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 10,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>test_MeanAbsoluteScaledError</th>\n",
+              "      <th>fit_time</th>\n",
+              "      <th>pred_time</th>\n",
+              "      <th>len_train_window</th>\n",
+              "      <th>cutoff</th>\n",
+              "      <th>y_train</th>\n",
+              "      <th>y_test</th>\n",
+              "      <th>y_pred</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>12.839683</td>\n",
+              "      <td>0.002775</td>\n",
+              "      <td>0.007933</td>\n",
+              "      <td>1095</td>\n",
+              "      <td>2022-12-30</td>\n",
+              "      <td>sales\n",
+              "date             \n",
+              "2020-01-01...</td>\n",
+              "      <td>sales\n",
+              "date             \n",
+              "2022-12-31...</td>\n",
+              "      <td>sales\n",
+              "2022-12-31  458.0\n",
+              "2023-01-01...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>3.813045</td>\n",
+              "      <td>0.002680</td>\n",
+              "      <td>0.006148</td>\n",
+              "      <td>1195</td>\n",
+              "      <td>2023-04-09</td>\n",
+              "      <td>sales\n",
+              "date             \n",
+              "2020-01-01...</td>\n",
+              "      <td>sales\n",
+              "date             \n",
+              "2023-04-10...</td>\n",
+              "      <td>sales\n",
+              "2023-04-10  866.0\n",
+              "2023-04-11...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>8.068216</td>\n",
+              "      <td>0.002591</td>\n",
+              "      <td>0.006612</td>\n",
+              "      <td>1295</td>\n",
+              "      <td>2023-07-18</td>\n",
+              "      <td>sales\n",
+              "date             \n",
+              "2020-01-01...</td>\n",
+              "      <td>sales\n",
+              "date             \n",
+              "2023-07-19...</td>\n",
+              "      <td>sales\n",
+              "2023-07-19  748.0\n",
+              "2023-07-20...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>7.854970</td>\n",
+              "      <td>0.002779</td>\n",
+              "      <td>0.005778</td>\n",
+              "      <td>1395</td>\n",
+              "      <td>2023-10-26</td>\n",
+              "      <td>sales\n",
+              "date             \n",
+              "2020-01-01...</td>\n",
+              "      <td>sales\n",
+              "date             \n",
+              "2023-10-27...</td>\n",
+              "      <td>sales\n",
+              "2023-10-27  1229.0\n",
+              "2023-10-...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>5.955709</td>\n",
+              "      <td>0.002442</td>\n",
+              "      <td>0.005910</td>\n",
+              "      <td>1495</td>\n",
+              "      <td>2024-02-03</td>\n",
+              "      <td>sales\n",
+              "date             \n",
+              "2020-01-01...</td>\n",
+              "      <td>sales\n",
+              "date             \n",
+              "2024-02-04...</td>\n",
+              "      <td>sales\n",
+              "2024-02-04  1916.0\n",
+              "2024-02-...</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   test_MeanAbsoluteScaledError  fit_time  pred_time  len_train_window  \\\n",
+              "0                     12.839683  0.002775   0.007933              1095   \n",
+              "1                      3.813045  0.002680   0.006148              1195   \n",
+              "2                      8.068216  0.002591   0.006612              1295   \n",
+              "3                      7.854970  0.002779   0.005778              1395   \n",
+              "4                      5.955709  0.002442   0.005910              1495   \n",
+              "\n",
+              "       cutoff                                            y_train  \\\n",
+              "0  2022-12-30              sales\n",
+              "date             \n",
+              "2020-01-01...   \n",
+              "1  2023-04-09              sales\n",
+              "date             \n",
+              "2020-01-01...   \n",
+              "2  2023-07-18              sales\n",
+              "date             \n",
+              "2020-01-01...   \n",
+              "3  2023-10-26              sales\n",
+              "date             \n",
+              "2020-01-01...   \n",
+              "4  2024-02-03              sales\n",
+              "date             \n",
+              "2020-01-01...   \n",
+              "\n",
+              "                                              y_test  \\\n",
+              "0              sales\n",
+              "date             \n",
+              "2022-12-31...   \n",
+              "1              sales\n",
+              "date             \n",
+              "2023-04-10...   \n",
+              "2              sales\n",
+              "date             \n",
+              "2023-07-19...   \n",
+              "3              sales\n",
+              "date             \n",
+              "2023-10-27...   \n",
+              "4              sales\n",
+              "date             \n",
+              "2024-02-04...   \n",
+              "\n",
+              "                                              y_pred  \n",
+              "0              sales\n",
+              "2022-12-31  458.0\n",
+              "2023-01-01...  \n",
+              "1              sales\n",
+              "2023-04-10  866.0\n",
+              "2023-04-11...  \n",
+              "2              sales\n",
+              "2023-07-19  748.0\n",
+              "2023-07-20...  \n",
+              "3               sales\n",
+              "2023-10-27  1229.0\n",
+              "2023-10-...  \n",
+              "4               sales\n",
+              "2024-02-04  1916.0\n",
+              "2024-02-...  "
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.forecasting.model_evaluation import evaluate\n",
         "from sktime.performance_metrics.forecasting import MeanAbsoluteScaledError\n",
@@ -284,19 +560,28 @@
         "    error_score=\"raise\",\n",
         "    return_data=True,\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     }
   ],
   "metadata": {
     "kernelspec": {
-      "name": "python3",
+      "display_name": "tsbook-py3.11",
       "language": "python",
-      "display_name": "Python 3 (ipykernel)",
-      "path": "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/share/jupyter/kernels/python3"
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.11"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 4
-}
\ No newline at end of file
+}
diff --git a/notebooks/part2/01_exog_variables.ipynb b/notebooks/part2/01_exog_variables.ipynb
index fb34047..5e2b4c7 100644
--- a/notebooks/part2/01_exog_variables.ipynb
+++ b/notebooks/part2/01_exog_variables.ipynb
@@ -19,7 +19,84 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 1,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>promo</th>\n",
+              "      <th>macro_trend</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2020-01-01</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.304000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-02</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.327826</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-03</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.350638</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-04</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.361667</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-05</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.361633</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            promo  macro_trend\n",
+              "date                          \n",
+              "2020-01-01    0.0     1.304000\n",
+              "2020-01-02    0.0     1.327826\n",
+              "2020-01-03    0.0     1.350638\n",
+              "2020-01-04    0.0     1.361667\n",
+              "2020-01-05    0.0     1.361633"
+            ]
+          },
+          "execution_count": 1,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from tsbook.datasets.retail import SyntheticRetail\n",
         "from sktime.utils.plotting import plot_series\n",
@@ -31,32 +108,72 @@
         ")\n",
         "\n",
         "X_train.head()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 2,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<Axes: xlabel='date'>"
+            ]
+          },
+          "execution_count": 2,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "import matplotlib.pyplot as plt\n",
         "\n",
         "X_train.plot.line()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 3,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<Axes: xlabel='date'>"
+            ]
+          },
+          "execution_count": 3,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1000x600 with 2 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "fig, ax = plt.subplots( figsize=(10, 6))\n",
         "\n",
         "y_train.plot(ax=ax, label=\"y\")\n",
         "X_train[\"macro_trend\"].plot(ax=ax.twinx(), label=\"macro_trend\")\n"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -67,16 +184,124 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 4,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>name</th>\n",
+              "      <th>object</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>ARDL</td>\n",
+              "      <td>&lt;class 'sktime.forecasting.ardl.ARDL'&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>ARIMA</td>\n",
+              "      <td>&lt;class 'sktime.forecasting.arima._pmdarima.ARI...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>AutoARIMA</td>\n",
+              "      <td>&lt;class 'sktime.forecasting.arima._pmdarima.Aut...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>AutoEnsembleForecaster</td>\n",
+              "      <td>&lt;class 'sktime.forecasting.compose._ensemble.A...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>AutoREG</td>\n",
+              "      <td>&lt;class 'sktime.forecasting.auto_reg.AutoREG'&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>77</th>\n",
+              "      <td>UpdateEvery</td>\n",
+              "      <td>&lt;class 'sktime.forecasting.stream._update.Upda...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>78</th>\n",
+              "      <td>UpdateRefitsEvery</td>\n",
+              "      <td>&lt;class 'sktime.forecasting.stream._update.Upda...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>79</th>\n",
+              "      <td>VARMAX</td>\n",
+              "      <td>&lt;class 'sktime.forecasting.varmax.VARMAX'&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>80</th>\n",
+              "      <td>VECM</td>\n",
+              "      <td>&lt;class 'sktime.forecasting.vecm.VECM'&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>81</th>\n",
+              "      <td>YfromX</td>\n",
+              "      <td>&lt;class 'sktime.forecasting.compose._reduce.Yfr...</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>82 rows × 2 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                      name                                             object\n",
+              "0                     ARDL             <class 'sktime.forecasting.ardl.ARDL'>\n",
+              "1                    ARIMA  <class 'sktime.forecasting.arima._pmdarima.ARI...\n",
+              "2                AutoARIMA  <class 'sktime.forecasting.arima._pmdarima.Aut...\n",
+              "3   AutoEnsembleForecaster  <class 'sktime.forecasting.compose._ensemble.A...\n",
+              "4                  AutoREG      <class 'sktime.forecasting.auto_reg.AutoREG'>\n",
+              "..                     ...                                                ...\n",
+              "77             UpdateEvery  <class 'sktime.forecasting.stream._update.Upda...\n",
+              "78       UpdateRefitsEvery  <class 'sktime.forecasting.stream._update.Upda...\n",
+              "79                  VARMAX         <class 'sktime.forecasting.varmax.VARMAX'>\n",
+              "80                    VECM             <class 'sktime.forecasting.vecm.VECM'>\n",
+              "81                  YfromX  <class 'sktime.forecasting.compose._reduce.Yfr...\n",
+              "\n",
+              "[82 rows x 2 columns]"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.registry import all_estimators\n",
         "\n",
         "all_estimators(\n",
         "    \"forecaster\", filter_tags={\"capability:exogenous\": True}, as_dataframe=True\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -102,25 +327,46 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 5,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from sktime.forecasting.auto_reg import AutoREG\n",
         "\n",
         "model = AutoREG(lags=30)\n",
         "model.fit(y_train, X=X_train)\n",
         "y_pred = model.predict(fh=y_test.index, X=X_test)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 6,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 6,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "plot_series(y_train, y_test, y_pred, labels=[\"Treino\", \"Teste\", \"Previsão com Exógenas\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -137,15 +383,15 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 7,
       "metadata": {},
+      "outputs": [],
       "source": [
         "import numpy as np\n",
         "\n",
         "X_test_missing = X_test.copy()\n",
         "X_test_missing[\"macro_trend\"] = np.nan"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -162,7 +408,9 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 8,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from sktime.forecasting.compose import ForecastX\n",
         "\n",
@@ -175,18 +423,37 @@
         "model.fit(y_train, X=X_train, fh=fh)\n",
         "\n",
         "y_pred_case1 = model.predict(X=X_test_missing)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 9,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "plot_series(y_train, y_test, y_pred_case1, labels=[\"Treino\", \"Teste\", \"Previsão com Exógenas Previstas\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -199,7 +466,84 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 10,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>promo</th>\n",
+              "      <th>macro_trend</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2024-12-28</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>22.805784</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-29</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>22.805784</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-30</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>22.805784</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-31</th>\n",
+              "      <td>1.0</td>\n",
+              "      <td>22.805784</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2025-01-01</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>22.805784</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            promo  macro_trend\n",
+              "date                          \n",
+              "2024-12-28    0.0    22.805784\n",
+              "2024-12-29    0.0    22.805784\n",
+              "2024-12-30    0.0    22.805784\n",
+              "2024-12-31    1.0    22.805784\n",
+              "2025-01-01    0.0    22.805784"
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.transformations.series.impute import Imputer\n",
         "imputer = Imputer(method=\"mean\")\n",
@@ -208,9 +552,7 @@
         "# Agora imputamos\n",
         "X_test_imputed = imputer.transform(X_test_missing)\n",
         "X_test_imputed.tail()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -221,7 +563,344 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 11,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-ad554a84-34bb-4a7e-bcca-3a7aa15d1674' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ForecastingPipeline(steps=[(&#x27;imputer&#x27;, Imputer(method=&#x27;mean&#x27;)),\n",
+              "                           (&#x27;forecaster&#x27;, AutoREG(lags=30))])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('4865f36c-04f7-4f9e-b0be-1aa597461b92') type=\"checkbox\" ><label for=UUID('4865f36c-04f7-4f9e-b0be-1aa597461b92') class='sk-toggleable__label sk-toggleable__label-arrow'>ForecastingPipeline<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.compose.ForecastingPipeline.html\">?<span>Documentation for ForecastingPipeline</span></a></label><div class=\"sk-toggleable__content\"><pre>ForecastingPipeline(steps=[(&#x27;imputer&#x27;, Imputer(method=&#x27;mean&#x27;)),\n",
+              "                           (&#x27;forecaster&#x27;, AutoREG(lags=30))])</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('f9251840-c186-476a-86cc-962b5f5bb3f8') type=\"checkbox\" ><label for=UUID('f9251840-c186-476a-86cc-962b5f5bb3f8') class='sk-toggleable__label sk-toggleable__label-arrow'>Imputer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.impute.Imputer.html\">?<span>Documentation for Imputer</span></a></label><div class=\"sk-toggleable__content\"><pre>Imputer(method=&#x27;mean&#x27;)</pre></div></div></div><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('77063a61-e409-413f-b1eb-0ac11fba3596') type=\"checkbox\" ><label for=UUID('77063a61-e409-413f-b1eb-0ac11fba3596') class='sk-toggleable__label sk-toggleable__label-arrow'>AutoREG<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.auto_reg.AutoREG.html\">?<span>Documentation for AutoREG</span></a></label><div class=\"sk-toggleable__content\"><pre>AutoREG(lags=30)</pre></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "ForecastingPipeline(steps=[('imputer', Imputer(method='mean')),\n",
+              "                           ('forecaster', AutoREG(lags=30))])"
+            ]
+          },
+          "execution_count": 11,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.forecasting.compose import ForecastingPipeline\n",
         "from sktime.transformations.series.difference import Differencer\n",
@@ -231,19 +910,38 @@
         "    steps=[(\"imputer\", Imputer(method=\"mean\")), (\"forecaster\", AutoREG(lags=30))]\n",
         ")\n",
         "model.fit(y_train, X=X_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 12,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 12,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_pred_case2 = model.predict(fh=y_test.index, X=X_test_missing)\n",
         "plot_series(y_train, y_test, y_pred_case2, labels=[\"Treino\", \"Teste\", \"Previsão com Exógenas Imputadas\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -288,7 +986,9 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 13,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from sktime.transformations.compose import TransformerPipeline\n",
         "from sktime.transformations.series.feature_selection import FeatureSelection\n",
@@ -305,25 +1005,677 @@
         "        (\"feature_selection\", FeatureSelection()),  # Seleciona features\n",
         "    ]\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 14,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
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+              "      <td>82.086222</td>\n",
+              "      <td>82.288000</td>\n",
+              "      <td>82.084889</td>\n",
+              "      <td>82.555556</td>\n",
+              "      <td>83.153778</td>\n",
+              "      <td>81.639111</td>\n",
+              "      <td>83.721778</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>79.001778</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>83.123111</td>\n",
+              "      <td>72.249778</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>76.692889</td>\n",
+              "      <td>81.764000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 180 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            lag_98__macro_trend  lag_34__macro_trend  lag_17__macro_trend  \\\n",
+              "date                                                                        \n",
+              "2024-07-06            82.233778            81.711556            81.654222   \n",
+              "2024-07-07            82.288444            81.823556            81.886667   \n",
+              "2024-07-08            82.319556            82.084889            82.160889   \n",
+              "2024-07-09            82.393778            82.555556            82.290222   \n",
+              "2024-07-10            82.383556            82.657333            82.144889   \n",
+              "\n",
+              "            lag_104__macro_trend  lag_67__macro_trend  lag_36__macro_trend  \\\n",
+              "date                                                                         \n",
+              "2024-07-06             81.633778            81.764000            82.488444   \n",
+              "2024-07-07             81.660444            81.880444            82.042667   \n",
+              "2024-07-08             81.724444            82.063111            81.711556   \n",
+              "2024-07-09             81.875556            82.175556            81.823556   \n",
+              "2024-07-10             82.086222            82.288000            82.084889   \n",
+              "\n",
+              "            lag_35__macro_trend  lag_9__macro_trend  lag_22__macro_trend  \\\n",
+              "date                                                                       \n",
+              "2024-07-06            82.042667           82.259556            82.534667   \n",
+              "2024-07-07            81.711556           82.540444            82.463556   \n",
+              "2024-07-08            81.823556           82.741333            82.210222   \n",
+              "2024-07-09            82.084889           82.909333            81.881778   \n",
+              "2024-07-10            82.555556           83.153778            81.639111   \n",
+              "\n",
+              "            lag_6__macro_trend  ...  lag_119__promo  lag_129__macro_trend  \\\n",
+              "date                            ...                                         \n",
+              "2024-07-06           82.909333  ...             0.0             77.054667   \n",
+              "2024-07-07           83.153778  ...             0.0             77.324889   \n",
+              "2024-07-08           83.440444  ...             0.0             77.896000   \n",
+              "2024-07-09           83.594667  ...             0.0             78.460444   \n",
+              "2024-07-10           83.721778  ...             0.0             79.001778   \n",
+              "\n",
+              "            lag_34__promo  lag_33__promo  lag_47__macro_trend  \\\n",
+              "date                                                            \n",
+              "2024-07-06            0.0            0.0            82.734222   \n",
+              "2024-07-07            0.0            0.0            82.791556   \n",
+              "2024-07-08            0.0            0.0            82.934667   \n",
+              "2024-07-09            0.0            0.0            83.110222   \n",
+              "2024-07-10            0.0            0.0            83.123111   \n",
+              "\n",
+              "            lag_159__macro_trend  lag_114__promo  lag_91__promo  \\\n",
+              "date                                                              \n",
+              "2024-07-06             71.103556             0.0            0.0   \n",
+              "2024-07-07             71.535556             0.0            1.0   \n",
+              "2024-07-08             71.861333             0.0            0.0   \n",
+              "2024-07-09             72.159111             0.0            0.0   \n",
+              "2024-07-10             72.249778             0.0            0.0   \n",
+              "\n",
+              "            lag_136__macro_trend  lag_71__macro_trend  \n",
+              "date                                                   \n",
+              "2024-07-06             76.021333            81.838222  \n",
+              "2024-07-07             76.131111            82.044889  \n",
+              "2024-07-08             76.268889            82.003111  \n",
+              "2024-07-09             76.441333            81.840889  \n",
+              "2024-07-10             76.692889            81.764000  \n",
+              "\n",
+              "[5 rows x 180 columns]"
+            ]
+          },
+          "execution_count": 14,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "transformer_pipeline.fit(X=X_train, y=y_train)\n",
         "X_test_transformed = transformer_pipeline.transform(X=X_test_missing)\n",
         "\n",
         "X_test_transformed.head()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 15,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-233c90e3-835f-4c3b-ae23-e82e24e12fee {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-233c90e3-835f-4c3b-ae23-e82e24e12fee a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-233c90e3-835f-4c3b-ae23-e82e24e12fee' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ForecastingPipeline(steps=[(&#x27;preprocessing&#x27;,\n",
+              "                            TransformerPipeline(steps=[(&#x27;lag&#x27;,\n",
+              "                                                        Lag(lags=[1, 2, 3, 4, 5,\n",
+              "                                                                  6, 7, 8, 9,\n",
+              "                                                                  10, 11, 12,\n",
+              "                                                                  13, 14, 15,\n",
+              "                                                                  16, 17, 18,\n",
+              "                                                                  19, 20, 21,\n",
+              "                                                                  22, 23, 24,\n",
+              "                                                                  25, 26, 27,\n",
+              "                                                                  28, 29, 30, ...])),\n",
+              "                                                       (&#x27;subset&#x27;,\n",
+              "                                                        IndexSubset()),\n",
+              "                                                       (&#x27;impute&#x27;,\n",
+              "                                                        Imputer(method=&#x27;backfill&#x27;,\n",
+              "                                                                value=0)),\n",
+              "                                                       (&#x27;feature_selection&#x27;,\n",
+              "                                                        FeatureSelection())])),\n",
+              "                           (&#x27;forecaster&#x27;, AutoREG(lags=30))])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('3468d391-0cb4-40c4-b49b-064e33a4621d') type=\"checkbox\" ><label for=UUID('3468d391-0cb4-40c4-b49b-064e33a4621d') class='sk-toggleable__label sk-toggleable__label-arrow'>ForecastingPipeline<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.compose.ForecastingPipeline.html\">?<span>Documentation for ForecastingPipeline</span></a></label><div class=\"sk-toggleable__content\"><pre>ForecastingPipeline(steps=[(&#x27;preprocessing&#x27;,\n",
+              "                            TransformerPipeline(steps=[(&#x27;lag&#x27;,\n",
+              "                                                        Lag(lags=[1, 2, 3, 4, 5,\n",
+              "                                                                  6, 7, 8, 9,\n",
+              "                                                                  10, 11, 12,\n",
+              "                                                                  13, 14, 15,\n",
+              "                                                                  16, 17, 18,\n",
+              "                                                                  19, 20, 21,\n",
+              "                                                                  22, 23, 24,\n",
+              "                                                                  25, 26, 27,\n",
+              "                                                                  28, 29, 30, ...])),\n",
+              "                                                       (&#x27;subset&#x27;,\n",
+              "                                                        IndexSubset()),\n",
+              "                                                       (&#x27;impute&#x27;,\n",
+              "                                                        Imputer(method=&#x27;backfill&#x27;,\n",
+              "                                                                value=0)),\n",
+              "                                                       (&#x27;feature_selection&#x27;,\n",
+              "                                                        FeatureSelection())])),\n",
+              "                           (&#x27;forecaster&#x27;, AutoREG(lags=30))])</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('b5044b60-cdb6-48ea-ae6e-f1502d3f8e1b') type=\"checkbox\" ><label for=UUID('b5044b60-cdb6-48ea-ae6e-f1502d3f8e1b') class='sk-toggleable__label sk-toggleable__label-arrow'>preprocessing<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.compose.TransformerPipeline.html\">?<span>Documentation for preprocessing</span></a></label><div class=\"sk-toggleable__content\"><pre>TransformerPipeline(steps=[(&#x27;lag&#x27;,\n",
+              "                            Lag(lags=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,\n",
+              "                                      14, 15, 16, 17, 18, 19, 20, 21, 22, 23,\n",
+              "                                      24, 25, 26, 27, 28, 29, 30, ...])),\n",
+              "                           (&#x27;subset&#x27;, IndexSubset()),\n",
+              "                           (&#x27;impute&#x27;, Imputer(method=&#x27;backfill&#x27;, value=0)),\n",
+              "                           (&#x27;feature_selection&#x27;, FeatureSelection())])</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('96848a4e-c3e8-4712-a0b2-a9d6b48f5b12') type=\"checkbox\" ><label for=UUID('96848a4e-c3e8-4712-a0b2-a9d6b48f5b12') class='sk-toggleable__label sk-toggleable__label-arrow'>Lag<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.lag.Lag.html\">?<span>Documentation for Lag</span></a></label><div class=\"sk-toggleable__content\"><pre>Lag(lags=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,\n",
+              "          21, 22, 23, 24, 25, 26, 27, 28, 29, 30, ...])</pre></div></div></div><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('e6b8b159-8a34-43af-9007-38e3dcd2095e') type=\"checkbox\" ><label for=UUID('e6b8b159-8a34-43af-9007-38e3dcd2095e') class='sk-toggleable__label sk-toggleable__label-arrow'>IndexSubset<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.subset.IndexSubset.html\">?<span>Documentation for IndexSubset</span></a></label><div class=\"sk-toggleable__content\"><pre>IndexSubset()</pre></div></div></div><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('c929d907-ea93-4006-b5e8-b4fe367468f3') type=\"checkbox\" ><label for=UUID('c929d907-ea93-4006-b5e8-b4fe367468f3') class='sk-toggleable__label sk-toggleable__label-arrow'>Imputer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.impute.Imputer.html\">?<span>Documentation for Imputer</span></a></label><div class=\"sk-toggleable__content\"><pre>Imputer(method=&#x27;backfill&#x27;, value=0)</pre></div></div></div><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('767fbdad-182b-41ee-8b57-acfeb82e7469') type=\"checkbox\" ><label for=UUID('767fbdad-182b-41ee-8b57-acfeb82e7469') class='sk-toggleable__label sk-toggleable__label-arrow'>FeatureSelection<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.feature_selection.FeatureSelection.html\">?<span>Documentation for FeatureSelection</span></a></label><div class=\"sk-toggleable__content\"><pre>FeatureSelection()</pre></div></div></div></div></div><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('bf1aff5a-5b4a-4ffa-97b2-93c861104b3e') type=\"checkbox\" ><label for=UUID('bf1aff5a-5b4a-4ffa-97b2-93c861104b3e') class='sk-toggleable__label sk-toggleable__label-arrow'>AutoREG<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.auto_reg.AutoREG.html\">?<span>Documentation for AutoREG</span></a></label><div class=\"sk-toggleable__content\"><pre>AutoREG(lags=30)</pre></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "ForecastingPipeline(steps=[('preprocessing',\n",
+              "                            TransformerPipeline(steps=[('lag',\n",
+              "                                                        Lag(lags=[1, 2, 3, 4, 5,\n",
+              "                                                                  6, 7, 8, 9,\n",
+              "                                                                  10, 11, 12,\n",
+              "                                                                  13, 14, 15,\n",
+              "                                                                  16, 17, 18,\n",
+              "                                                                  19, 20, 21,\n",
+              "                                                                  22, 23, 24,\n",
+              "                                                                  25, 26, 27,\n",
+              "                                                                  28, 29, 30, ...])),\n",
+              "                                                       ('subset',\n",
+              "                                                        IndexSubset()),\n",
+              "                                                       ('impute',\n",
+              "                                                        Imputer(method='backfill',\n",
+              "                                                                value=0)),\n",
+              "                                                       ('feature_selection',\n",
+              "                                                        FeatureSelection())])),\n",
+              "                           ('forecaster', AutoREG(lags=30))])"
+            ]
+          },
+          "execution_count": 15,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "model = ForecastingPipeline(\n",
         "    steps=[\n",
@@ -334,29 +1686,59 @@
         "\n",
         "\n",
         "model"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 16,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 16,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_pred_case3 = model.predict(fh=y_test.index, X=X_test_missing)\n",
         "plot_series(y_train, y_test, y_pred_case3, labels=[\"Treino\", \"Teste\", \"Previsão com Exógenas Lag\"])"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     }
   ],
   "metadata": {
     "kernelspec": {
-      "name": "python3",
+      "display_name": "tsbook-py3.11",
       "language": "python",
-      "display_name": "Python 3 (ipykernel)",
-      "path": "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/share/jupyter/kernels/python3"
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.11"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 4
-}
\ No newline at end of file
+}
diff --git a/notebooks/part2/02_ml_models.ipynb b/notebooks/part2/02_ml_models.ipynb
index 2247392..0a31211 100644
--- a/notebooks/part2/02_ml_models.ipynb
+++ b/notebooks/part2/02_ml_models.ipynb
@@ -28,19 +28,21 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 1,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# | echo: false\n",
         "\n",
         "import warnings\n",
         "warnings.filterwarnings(\"ignore\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 2,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# | code-fold: true\n",
         "from tsbook.datasets.retail import SyntheticRetail\n",
@@ -51,9 +53,7 @@
         "y_train, X_train, y_test, X_test = dataset.load(\n",
         "    \"y_train\", \"X_train\", \"y_test\", \"X_test\"\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -66,7 +66,20 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 3,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "# | code-fold: true\n",
         "_X = [y_train.iloc[i : i + 7] for i in range(0, 700)]\n",
@@ -100,9 +113,7 @@
         "ax.legend(handles=legend_handles, loc=\"best\")\n",
         "ax.set_title(\"Série original - Magnitudes diferentes para cada janela\")\n",
         "fig.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -115,7 +126,20 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 4,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "# | code-fold: true\n",
         "\n",
@@ -131,9 +155,7 @@
         "ax.legend(handles=legend_handles, loc=\"best\")\n",
         "ax.set_title(\"Série normalizada\")\n",
         "fig.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -150,7 +172,352 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 5,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000487 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1618, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 580.233004\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-b3233497-39d6-4161-94e8-feca85c4cabd {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-b3233497-39d6-4161-94e8-feca85c4cabd a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-b3233497-39d6-4161-94e8-feca85c4cabd' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42), window_length=30)</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('f00b20f1-5665-46d0-b2fb-c51ce3d589c5') type=\"checkbox\" ><label for=UUID('f00b20f1-5665-46d0-b2fb-c51ce3d589c5') class='sk-toggleable__label sk-toggleable__label-arrow'>ReductionForecaster</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42), window_length=30)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('47c72031-bf3f-4ccd-8325-05636d13fa6f') type=\"checkbox\" ><label for=UUID('47c72031-bf3f-4ccd-8325-05636d13fa6f') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('24c8e5a0-cea0-44dd-9278-89d9d53c1a72') type=\"checkbox\" ><label for=UUID('24c8e5a0-cea0-44dd-9278-89d9d53c1a72') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42)</pre></div></div></div></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "ReductionForecaster(estimator=LGBMRegressor(random_state=42), window_length=30)"
+            ]
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from tsbook.forecasting.reduction import ReductionForecaster\n",
         "from lightgbm import LGBMRegressor\n",
@@ -161,20 +528,29 @@
         ")\n",
         "\n",
         "model.fit(y_train, X=X_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 6,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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7xYSWfio70+EMRzU/9BuORpbHxM95NK3cHtWYVsC5NJwfDSst4UBQlgZLzcbw3of+SQqHH62JZPMD3MLJUH3MVa3QvDF/X1kdLDGvNCC0RX5T864cHlwvYV0OZDuGVnleVTNOlpbsFxM+Rk4mJFXLXjHzI8ONNeamF9eskHOCe0Y+oEBAFjVVhf6i5mO5sXZz5GlxcznNra6fibMNvPl759IdtoS3emB5zDGRYanJ6AIetw3iAAAAAAAA6dAAMnEWIdK3OC86j1KjOWspjQaKXqGlW4Wk+scpu/oOHZ3HbklYqTM1tU1dKz81THUGrt3zs2VzTSTIG9g9X+48emdfr6fLY3SjtzO01FbuZNWYGhBq4Gc+5CZaYbl9qFwKhh5ulus426uTVVhqWKkBYvQ+Efk2q8Tcdl/9OzK5bm708RpW/vitRyWQ1VPCEoi2pN9b+Uo0tIwErM1TD6/77M3IUa1zbkp3/5w/UfbatFUO0JtyiiVcFwkvm0Xa2xOxh5IaXjZWrY9e//6/V0ogO8+1atWi7+f6ubNkUcUGGVXSR66aMFmOGzo24Wt2Rb5nWIZCIV9fhJUAAAAAACCTnp9nW7LiQgvp4m7zsZTGqpDMy46NR3SJT6JQUas3rYU/zi3dbrelsgX886Yt4Hqp16fNWBi9zwor1cpNNUl3b2u15KrHJkr991+4VlhqK3eyakytZrSHlXqfVlheUPOBhOoqmm5yBJSOANNZYXl3/h4eP7Sw/DF7XNPjI+9Vw71IfNrckq6P+13+vs4XiH73VZW2+jumiza9h6s355nLvD5Nr9P8gGh7eyJ15rOM2LLwEalZ9Xb0euOWlXFzMO2s8PXz8jVS29hgLvV6vyeuNvehhUt3AAAAAAAAWsv6rbWe91kLdtZtiX+Mn6U0Glr2KYpt5d3jrnddQ0crONTqTWvhj7NC07ot1dDSawGQLhS65KUF8ct9xD2M/fWHM6To0csl6+FLpfc7b8sNW0rcW7R1MuWIY1yrMePCPrumnFEDxOplr8qKv4yID+hcKyybA0udKxkbglqnFJClgeLI45tmWGolYly0GQjIt1ndHdvKm2lVqGsgqpWcjdnNszJtsosHS9mUp10/E4u+z63z/9r8nrR1PfZdmv+rczDdaPjqZkNtpQkuCS0zEFhWVlbKq6++Kg888IDcfffdMV8AAAAAAACZ0qvQfeOz2m9YT9MWrS3UTr6X0lTHzldctH6ra+iooaJz4U86lZ2pLgDSjehxG8IlPozVsPLW+bOlpimgrJMs0wZ9S94+rmcadgn1Sk2FYdi7GrJp6Y5WOB7R7WQZFZgie7z7akx46FywE9b5lrYZl56BYjgs20tVTJWmtk270mpMPTcX8VWh8WpWvhVzvWHLco+fqFu7fGJ13y90vV3D10Su/8w90OyK0gosP/30UxkxYoScfPLJct5558kNN9wgF154ofzmN7+RO++8M/NnCQAAAAAAuqy9hpTGXLdnUf/6cr1pwz5kZO+4x/hdSlNZ1+grdNRQMVkbtt/KTie3wNXOrcLSGcbes/A/4vYh/C1vnMeJxldC6vzF4nHnRK9/k9UzLvzTlnCtcNR5knWB7OhcyWhoGdci3uAvUAwE5KLsFU3HiDxHZzy6CgTky2Bv1ypLnW1ZGnJbqqPLfZra2OMP6FkZmWx5Ufypua+M8QxfmyzenDjQ7ErSCiwvuugiOfLII6W8vFwKCgpkzpw5snz5cpk4caLceuutmT9LAAAAAADQZW3XvSD6fTAgMqC4eTNzKBxpw7797WUxzxnbrzjpxm6toBx/62zfoaOGisnr6/xXdtrpgh3XY4nI4NIC1wpLZxhrVVY6T6bWY+eysxLSkttrx+j3ZTm58dWQej2ssyzd50o6l+44X0cDxZ/UOmY2Wq/RtIVbF/loC/Ye//mZ9A85W6+b31tMUGpzeY0jvI2+h4BHK3nyDeFJ2+WjL+W+jNozfG3SGA5J4d8ul11euK3Lt4enFVjOnTtXLrnkEgkGg5KVlSW1tbUyaNAg+f3vf2+qLAEAAAAAADJBQ8V/fPpt9PrIPt2kMDfLtSLS7n+/2j9pWKlt3/PXbvEdOmqo6LfC0k9lp1NhTmxMY7Wf/2T8APfXcVzPCWTF3xgOS564B5Pusy1FQrWbzKUGeyvrG+M/XL3uclt0rqTzuLb5lZY52YPinq+t5nfU9TNXq7+ZaRbY6Hbz/6v50P38m97fxYWHxYWQuzesjj9nnWEZLPYIOZNvCHe2y7sLSG7PnVzv0W3gl+48yfOZ9aGQWcYzr2kZT1eeaZlWYJmTk2PCSlVWViYrVkTKdbt37y4rV67M7BkCAAAAAIAuyQoV7TMmv1y/VZZ8Fz/v0VkEWKVBWwLOeZR+Qkdd0PPgCc3t1dla7uliaGlBwrDU631W1TfPeZSmykqtEp25aH3SpTt6jLr1/c0d0c9CvwkEZGrtZx5v0v0zCtVujs6vDLhUVwY9nhedKxlXYRkfWH4bLIl/eiAoS8JWNW3zpNCtgdilSHEVpIGsuBBySyDP8/HqV4WHy8zsESltCNd2+cIRxzXfEF3cE/B9nFt2nyLZgcRxXNgcKdClZ1qmFVjusssu8uGHkXT7gAMOkOnTp8vjjz9u5ljuvPPOmT5HAAAAAADQBVmhopO2gTs5H1edJLBMNI9Sl/x4tZMfMLyXJLPWZWN5Ou9TN5+f8vgnpuU92dIdc4z1wyW8YWA068uSsJxV85FMq30vpZZwK7DUbd5W23dUICAhrzhJt3zrc0KhhK+jwWKjW2gXDkufUGXcY28tiLSae9PqTPsSnoBUWIGlx7bwhkBQzi36kdySv7/k9h6bdEO40hb1qq+fa76haTGQbhgPZOX5Pk6DbQGRl7CEu/RMy7QCy9/97nfSv3/kj/bGG2+U0tJSOeecc2Tjxo3y4IMPZvocAQAAAABAF+R3yY0KpxhYJlpy831VvVw7a1HclnDngp7Sghxfy3DSfZ81DSHz5Xaf83Wix1g/XGRzX3ObXn87Z4jHzEb3CksN5bYufja6zdutwjIREzgmaQn/Xf5+7sext5V7bSn3oMHqsqye0eDwv8W7Ro/pLnL7n/MmyAf7Ppw0ZHTfEh6phQzmdZeh52+R7U79KOlxnl3mUe3qYlT3Mumq0gosx4wZI3vuuWe0JfyBBx6Qa6+91oSXEyZMyPQ5AgAAAACALsjvkhu39uxqR3u10+RR3mGQxlBa1aht2s7QsrKuOYz7rrLO1zKcTL5Pr9fpW9xUUVi8QQKl68y3oUAwfoO3/RiOYFHDSp0bGa7bHN3m7VZh6R0CiufSHX39I7qdLCNLzpVvs0q8j2Fb3mNVeSZ7PUu/br1NcPjOiLPlgfBQ8evSD1/09Tj3LeHJl/VYdCblibP/7vu8rppwqHRVaQWWRx99tPztb38z32/atEn22msvuf322+WYY46R+++/P9PnCAAAAAAAOjAN/SbcNlsKL3/FXLpVLrrxu+RG86wRvWMrJqtslZBuZi1an/B+a5GPfU5k5HnNbbpukehPxvdPaX5lKu/T7prJI6Ovo5/n8vLqyB1ly2MKEsNNy2ya26VtHIFlpIIwdpv3NVX/Tum81gW7xVVuvrBqsQlNFwV7S8gsBkrwbh1Vllrl6afC0u6GLz5K6TkrtkaWDNn9+sMZkv/INMl6+FLz1e+Jq+X17j9wGT6QfFmP5ZL/veT7nHKCQTl2yFjpqtIKLD/55BPZb7/9zPfPPvus9O3bV5YvX25CzLvvvjvT5wgAAAAAADqoaTMWmkrFz9dsMe3NXpWLbnTJzbNTd5P87Ob4wm3PjWZT5+4zNKWW8C/WNc9/9KLHtc+JVH//eFXC5/zz87UphbLW+3zilKYWZg/Ot73nkFL3GZi5VXEFibrMRmdLJquEjFQQxprYuDbp+dsOKA2BLHm1LrYl/oYvmwJE68SSVUw2zaPM7T1O9q9fEfv4BEHkuurIxvel4XzfVZluNKy8df5sqbfNmtxQWylnN46VA7pNldElvzTVopGlPcmX9VjVlSsqy9M+p64mrcCyqqpKiouLzfezZs2S4447zmwN10pLDS4BAAAAAAA0tLt19pKYDyIy9S++cjFRmLd9r8KYhTvH7Nwv5jH3HLuzHDi8d8xt1Q2NCc+r3m1zj4NmXs55lKs31yR8TmM4nFIoa6modV+AY3GebUNjOFq5qmFw9P66wvhMLxw2n/nMvB0TVlhml8a3skc3dPupWDTVnGG5sy725/PV1s2pBYhNy3s+2Och+XP+xObXbgo9izW1dpyPVpHukB851+0DNSlVWA7uFhvm3rPwP56P1Xb2ukC2qRbVpT1z9rrP1/zL6+emtvF7dI/Yz7CrSSuwHDFihLzwwguycuVKmTlzpkyePNncvn79eikpiV9LDwAAAAAAuh6t/HPj3HCdTG1DbPN1n25NIVqTfYf1kgZHAJmowtLrvOLOMxw/j7KsW17y53m0k3vR4PHsZz9P+Jj9t+8Zc/3dZd+ZUFTDUbvxm2oj2aAj5KuVLDk3f3LMLMtwODawLHWpFIwGlj4DR21BXxIuiLmtb25+gifEB4saPm4fKpdrPng6svTHVpmp95XoYh+9rem5+hitIj2/5n/m+pU77RZzvvoc1a2xxvU1b9vjqJjrNR7b02NPMnL8366IzAtNZlGFv43f1llf1YXnV6YdWE6fPl0uvfRSGTp0qFm+s/fee0erLXfZZZdMnyMAAAAAAOiAdHO1l1Q2adc1xgaW5VX1ceFkfSjke4ZlovNyCjuCRfvSnVTbyb3EtHT7POcnP11tnmM/v8n5c+S5gtvlj5WvNN/oaMO+Kn9S832h2M+oaMSxUjLxYtfAclSgUgJNr2YFgF5h4/BAVcxtVY0JPjNHEKrP1/DxgpoPZFFVddzSH71vQzhX7q18RUrCtea2PuFKua9yhhy8+b/mel6/PSVbmt5bOCwDwlvlz/nLZO7WP5nn9QtHfi4lOfny7EFT42ZF5gT8x2XLK8ujcy6HPX2jaf12M6qkj+vPeGi3UnnmwKkyrmd/yc/KlrE9+7ueU1eTVmB5wgknyIoVK+Sjjz6S1157LXr7wQcfLHfccUcmzw8AAAAAAHRQuv3aSyqbtOsaY4Oxf325Pi6w1BZpu8tf+cKzJdvvVm57laQeSysaN9X4Cyzd2skThZHJGpjXb42Ec5Y1FTVxz7mg5GnTMp8o7Pk+qyhaZencEq567XezBHK6xQWWQ4P10iMUqVCMNJjHsyodLwx+YzaOr3psojx43zjZWF/nfULhsPRpbAp2w2EZFfrOhI/6GjoPM771OyzDA9VyWMNSObo+Uil7Qt1CmdywzCy/0cDwx289Kg3hyKegZ/ptsETqvlsYXSR0RU2k5XtcYW5MMKjPLf37b2JmV6ZCZ1Tqa7uFlkO79XT9GZ8wdLwcN3SsfHr0JVJ5+s3m8tguHlamHViqfv36mWpKnV1p2WOPPWTHHR3zEAAAAAAAQJek26/dTJs0PKVN2lsc8x0rHdWTGli++dXGmNtWba6JmyNpzXzUhTv28Mir29leJemnCtJ+PLd2ci9+AtSg4yT7leTFPWf7nNXyes5ws5E72UKbyPdeVajNn85WiQSW5TVbZVMg37Vq0zqPwaHNJmw8tO4rWT/jRKnfOF/uyt3Fe55kU7v3WXUfm6s9w9UyM3++HJ5dIXfrOdrbwZserxWXvx05wZxj96YKy83mvCLLb3RWpKkEbXqe25b07uFI8Lrh+6UmWFVW0FnRkCBc9enSD1+Mua7HfmnlAtfHzlrtbzxBV5N2YAkAAAAAAJBsYc5ffjI+5rb7jhsrN08ZndIHV52gvdvc3xCSv364wleFpM58tC/c0VhrXL8SGVJaEBcA2qsk/VRBWvR4/5y6m+9QVoPdZMd2zuicMrpv3HOW1g8wQV/M3EenQEC+DPY2m673ePdV12rA1wLbmS3Y+piH8iKj//6XMzDpOV5dM1smNyyVxiprrmNYlgR7ep7LdqEKua/yFTm0fqm5XhXINXM0Q/VbZJluNXc+LxCQ7HCj7Lf0z6Z1vbQwMtdza35fKZvytFl+88XmdXEVoM4t6V8EIwuaFgV7yU7vvmFauTWszJQVWzdFv9fP97S3H/d87OLN/mZbdjXZbX0CAAAAAACg8yqvjp03WZNge7eXZEFZTX2jrNxU7atC0nmsHgU58uklB0QDTefzrSpJrYLUsDPZueRnB83xUg12T95lO/nHp9/6fs74Ad3l2am7Rc+5R362PN54iiwLboqb++hGN10v2LLZBHWX7jxJZn27yCyGKc7OlY0Fh0erG7+TrMgTPEJQvaUgmCVVocZoNaaEYn/mbpWSOmPy7a1/Mz+R8qbKzZpAtqyecZJkS1iGhcplcbB3zHvRSskRoe+l/rsFUv/dfFm74+9E1qyVl8P9ZN/5S2ToNw83zTK1dtFbzwubJT5K2+FvKdiv6Y6AfCsFIpWR+zJJg8pfvveMbKiNnefpNKp7WcZfuzOgwhIAAAAAAGwTGgJe+nJkdqDl4pcWes6WdBNyVBa6qa4PycDu8Zuo/VRIaqCq56OhoQaA/YsjW8BLC3JiqiSTVUFa8Vjvotxo63nh5a+YSz/vd1jPQnP5wx39BVj1jSE5Zky/6PXDdyyTOeH9pKQ+FKmwdGPdbrVLN9186/zZMq98jdQ2NshGK2BztH27Vklqi7aIDA99Z67+rmA/U5Wp1ZkaDOqXmUPpUimpn1hu77HSbcwZUhhuDjhfzh4p+3ebKoussNKxCVyX8eiZz8weIX9es9bcF5KwfF6+xtZ2Hd9GHnmeNFegpignGJQ++ZGfkfho39cgOFlYqbr6NnAvBJYAAAAAAGCbcJv7qNetNu10NoTb5WYFozMsT5ywXdz9zgpJr7pDa9alhpaXH7yDue3QkX1iWrqtQLNbblPFocPAHvnRINFqPa9pCJlL5yxNN1X1kcrTsf1LzOsEfLSI22d5hps+q57flUbmNrrFqwkqL1OP8ETypMHMrMytjwRzawPdTOXm4mAvM0fzd/n7ec6vHNNrkGx36kdSs/o9yZNGyWmap3lZ0WGyOqt7XFBqbQLXlnN1d/7u/oLHQECCEpJjhowzV7XV3E8Fqt3Rg8dIzdTfy9qTrzPVqBpeJtLoMxC9bOwkFux4ILAEAAAAAACuNGQbdsPrknXpy+Zr2I1vpFQd6VbVqNetNm3763hVJNoDy4Kc2Bgj1BQM/e7Nr6LfW/oU5fqukLTPurReQ0NQJw0td/TY/H3PsZHNzt9X1ce0nocdx/dS1RQ+FuZkmdcZ2784YWhZ3xiWitrmykQNSmsbQlKwtUTurXxFBoZdqvvcgrQ0qg0tvUPVZl7k/OymqlDbohs97rfBYs+Q1KosbKhYZioxG5NEtN8HCmJmU6YSPOZm5UrxuF+Y77XVPJX3nBUIyHMHnxG9fsvuU0x42XjGreZLA8x03bzblLSf29kRWAIAAAAAgDjWTMflm2pM6KZfy8urfVULWrSq0UkjJqtN2/46XhWJGsJZ9hzcvDjFvohm7ZZa+f1bS2LuO223gXEVkoeOjCxbSTTrsiAnK6biMdnGckv3/BxzqQt9wgmO78UKSAubKjiTtaA3hEIx51JR02DC3epwrhzWsEROa3QJSN0CPlvbdVKOx60OFptKytpAtvtxPQLFod1Ko5WFrxdMMMcIJQkstbVcH6fhpv4WmeDRp8ZwSAJZkVb/C2r+l7DSNOYtiMjOpYkXJ+nsz3SkVuPZ9RBYAgAAAAAA13ZuL35bujV0c9LIy2rTtl4nUUWiVWGZHQxEw0Q/AZBWINppAPr64o3uz7XNutQKR68KS1XhFVgWREK7oOZ0CY7vpbKuIeb1NWC98pBIe7oeryQ/O77Csqb5XN78aqNsqWmQmlCeCfV+lx3Z7m34nGmZiNvm8eiMSb+Vm0233Tiob+Q9f/283CnDE281dzz/j/l7mNmXhw+eIH6N7tEvGlhqmKubxv0I+5gxuXCztRE9NUO6xYbviEVgCQAAAAAA4nyxzrsi8PM1Fb4Wymjopl92WQGRa2ctij7PtW3cVpFY1xC5Ny87aDZwe3Eew6q+9BPA2mddFiQJLK2qRg0m7UrycqLBqtv7sYe0iVrCi2wzMnWOptqhT5HsP6xX9HOw3t9ts5urSq0q2D3yFsQvlvEKA3XWZdjeaC0yOL/INWwcEtokWeGQ/0rKBNWce875pQkry+fckNpMyUBAlmX1MrMv36rynm3qpKFjIKtpg7mInBlYlvDxWYGgjOvZX549aGrSGZPZaUZrt+5xVFrP6yoILAEAAAAAQAwNE7W12Yve43ehzJDSgpjrWvj4edPz8qbNcH2OvSKxtrExumBnQ2Wd5+sEXFqm7TQY9XqefdZl8wzLkOvG8q21jdFN0BYNKe1B4lOn7Rq9r0dBdszxvVQ5WsJj2tPrGqOVplYF5vw1FfLM5/Gf+xnFM1IKAfVx9p90UXa2a9j416zPZXCBy5bsFCssdVGPfuqb5twoDeWLTWu3763d4bBsL5Ege1HFBl9PsdrPa759N3rbZVv/Lb/abjszn9IeUuoSHJ1LWfez38unR1/iayFOo/gPTvXV/AahXZ3LkAEAAAAAANCVJapGtDPt200t4s5KSosGm140FHUGo6Y9PCwyeWQfU8H55fpIQKVLdRas3ZLwXBK1hOs8TQ1KnUb3K44JExNVWD7x6SrXCk79/vXFkQBNb95c3dyq7bGv24S8+jlrkKrnZm38tgJJ57noUh1zf26WlFfXy3+Wfe/6OQzNXmtCwMXB3ilvw1ZfbN3sevuicVfIL/N6yWUfvtz83sIhCQc8auE8Kiyn1nxmflr15Ysku3SkXLDpQzm36Ef+Ti4QkPMr3zHVmaNK+sjn5d5BeeRzD5tKRn38929f2nxnY42cv/DX8tuJF0uv/W6Wltipe1+ZV77G15b1ZwgqfaPCEgAAAAAA+KpGdOPc+u3c+P3lOu+Q0Y2Gd5dNGi5/mL3EVHDWNQWPm2saZHNN81Zsp1/sOTjmemNToGidj1fYebWjVdte1Winxzn9H3M9X/+2t5vbs8969vPo9xouOqtQ3RYNLfmuyqXCsrna01lhqdvI3SytHyDn1/zPhJUaKGbKvd8sksLsSNu7ZUBoq/wpd7Fc0L+vBBPNhWyqwjyr5iOZVvueiRNzSkdJ6V5XymENX8t2jRW+Fv/o7MnJDUtNdeZVEya7PqZPfpHkZ2XL2J79opWM2nrupuLj202Y2RJ6HpHg3jsc1nOiqjI1VFgCAAAAAIC40FBDNJ+NutH2bSuIs5bopHIMy19PnCA/ffwT873zuV6RUHFetjQ6Aq9l31dFz8eLtnKfMH5AzG3RpTsNsQGcczmQ01cbm0Ne5+O02PCSFxdEKyqtMNW+aMjyf898JjdPGW0qVqMVlg3aEh55lBVcOt+v5Z2aCfJ/uS/KvZWvmAU1XwabNqOnUW1p9+WWcjn3/edi3uO3WSUSalwu1w3pLzNXzZfFWb0ldiJm8weQG26IhpX6jnvsdaUUjThGyqY8JRvffSfp3mwNX0eEIlWldd8vlOOGjpVnDpwq1382SxZv3iAju/eR6RMmu7Zaa+u5Fw0/i0YcK+lynkffAv1bCMi66i0JzwntuMLypptukt13312Ki4ulrKxMjjnmGFm0KLbsvKamRs4991zp1auXdOvWTY4//nhZty52A9OKFSvkiCOOkMLCQnOcyy67TBoaYrd2zZ49W3bddVfJy8uTESNGyCOPPNIq7xEAAAAAgI5Gt3unEjRaC2XcNn6n6o53lsry8mrX+7wCzNKCbPnr/1bG3Kct0+fYKh39am7Djp+Bmej97NineQu429Kd5ZuqoxWVieaDaqWlVZFpnYs+/6OVm8z3Xp+Nmpw/R/6v5EXz+roNe8bWf8i9Va9Gl92kLRyW7EAwJlI0VYXhkNzVOFiHe0bmZnqEjjqjcvtQuUggaDZ8l0152oSVSsPCvkW9PV/X3np+Qc0HkdtDDaYyUsNCnTVZefrNCWdOauu5F21Nbyn7eSz98ZWy9Me/TXpOaMeB5dtvv23CyDlz5sjrr78u9fX1MnnyZKmsbP5fJS666CJ5+eWX5ZlnnjGPX716tRx33HHR+xsbG01YWVdXJ++99548+uijJoycPn169DHLli0zjznwwANl7ty5cuGFF8rPf/5zmTlzZqu/ZwAAAAAA2jut7nt26m7SzdaebP/ebtqk4dEZkMlCPT+edVkkY7EvutHvBjct9NnosYwn0ZIea/akc9P5G19FZlFqFeT4W2fLtBkLzWNqE8ziVNMnjzQVm4n4+WxMEBiIzAWdtWh9Ss+9oORpM0PTfhYaXJp27ZZUWAYCUhNqiA9iA0FZGu4mEm40czNdzzIcNu3pGjb23O9ms+HbCiujh/d4d9kSMpWZo0LfyX2VM0w7uPUMrYz0S1vPPd6YaU1H+xMIh1sSsWfWhg0bTIWkBpP777+/bN68Wfr06SNPPPGEnHDCCeYxX375pey0007y/vvvy1577SX/+te/ZMqUKSbI7Nu3r3nMAw88IL/+9a/N8XJzc833r7zyisyfPz/6WieddJJs2rRJXnvttbjzqK2tNV+WiooKGTRokDmfkpKSVvksAAAAAABoa/vd8x/57zcaRIn0KsyRu47ZWU594tPo/X/9yXj52R7NsyM12PNqA794/+3lwTnLzXKZ3kW5niGjX0fsVCbn7jNMfvTQBwlbtZOxnqsBrUrUQp6ohf7LXx8k2Ze9bALDTMjPDnouCvKycLuTJC8QP9vyiG4nyyJtDW9hW7iTVj7uGCqX9/bcR554+zY5t+gIz9mTX1bcK70Ovl9Kxp4Zd3/h3y6X2sbYTlmlYeXCivvcXzsrT4ae7/+z+e7dy83MSudP3l7tiW1L87Xu3bv7ytfa1dIdPWHVs2dPc/nxxx+bqstDDjkk+pgdd9xRBg8ebAJLpZdjx46NhpXqsMMOMx/CggULoo+xH8N6jHUMt1Z1/QCtLw0rAQAAAADozJzLcvS6NTfRapEudyx6qXOkc85Wcns8dsDwXrLfsJ4xLeQt8d435fLhykiYmpOVfhBnr2j0ux1d9SnKjX4/sHuk0jNTYaWej84FTWX5kbVwx60s7YKa/5mDui7hSbOOzcR9gaCcXzPHtGhrJWdPiQ8dVd9QZClTMKfI9X7d+O38Ceq5RtrItbI30OLKSN0GrvMyc3uPM2GnszUd7Uu7CSxDoZBp1d5nn31k5513NretXbvWVEj26NEj5rEaTup91mPsYaV1v3VfosdoqFldHT/74YorrjDhqfW1cmXsHAwAAAAAADoTt63Ven39lubuw6r6Rjn/hebORXX2s59HW6Y16NTA7yfjIu3h0tSyPbg033yv8xiLciO7f9dtbT5uunT79tUzI8tUSvJit1db/MaYmtnppvNUAsJzfjA0+v3sJRvNZ5CkI9wXa9ykhrpaYZmKuyt+4jquUsNEXcKjrdV54UYZlJsdDS97hyPbyf0GmPoWdQv3mMKCpjbtJfL9fyNj+fIbHcdyCOYW+9q0bYWh0ZmV8c3oZmlPqnRepraka2WmW2s62o92E1jqLEtt2X7yySfb+lTMYh4tTbV/AQAAAADQWpWNrc1rWc7KzbFFPm553K2zl8QEnU/bZlB+u7lG1lZEwsn8nKAUNc3BXGcLQlvCOh8N6SYN7xVz26Du+b7bxPU5WtGYSkC45LvmcFMrK/W9p1thedzYftHvx/Yrln9O3c3MBZ08qiyl48yq2UserDg6ElpGb418ItYSni/qn5J5E3aSQaEKc/s+DY4irURt4+Gw7CRbZf0P9pQX1twSnSkZrossBNoYLHR92oZg5HMNeASW1qbtsT37SV4gIKMaNzTPrNT5mzZZRf2ojOwC2kVged5558mMGTPkrbfekoEDB0Zv79evn1mmo7Mm7XRLuN5nPca5Ndy6nuwxGkQWFETKtgEAAAAAaC+Vja0dWnoty3EGcF55nNdWcF1qY7WVv7+8XAqaAssNtgrLg3fw2BDtg/V61Q2RuZjqoKbjDSotkPP3Ger7OFrRqC3tfhTkBOWtrze6nku6S45UblZQ5l4yyYSV+jugYbAX+4KfotzmeOf3FafLLzdeJl/UDZFQMNL63H33K6L3BwJZ8vLmKlnfFCLOzBnu/0QDATmv+r9SPucG1/haF+/oRnDX1m7TEt68Sd1r0/bi7H/LjK1P2hbsxIqsYmk361jQGQNL/SXTsPL555+Xf//73zJs2LCY+ydOnCg5OTny5ptvRm9btGiRrFixQvbee29zXS/nzZsn69c3b87SjeMaRo4ePTr6GPsxrMdYxwAAAAAAoC24VTZa8xRbU9/ivG3+Glf960tZvbnGfL9+a53rLMhUWZFZTX1IttZG5id2z4+0nTc0huWNr2JDRS85wYAJCTU4PGpM7Eg5NxO36x7zHjLR3m5VoVqSzdPUMNgKT3vkx36GM2v2kqM23C4n1M8wrc8Fgw+M3vdacLCctmiJ1Ejkc7Iu4zhbw8Nh2a5xs0wpyZOG8sWuoaHOytSN4Fa7uV7aW7vXv3a6VH79fOL35XFsS6hqnayfcWLS46BjC7Z1G/hjjz1mtoAXFxebWZP6Zc2V1IU3Z555plx88cWm+lKX8JxxxhkmaNQN4Wry5MkmmDzttNPks88+k5kzZ8qVV15pjq2t3erss8+WpUuXyrRp08yW8fvuu0+efvppueiii9ry7QMAAAAAuji3ykZrnmJr0Uq+5eXx+x0yTSstX164Lm6G5feORT5eXcl7D4ndb6HCtvBuc00ksCzJz4netuS7xDMVrdca3a+5VfmFM/aQSycNj6lgdMrJCkr/krzMB5bZzTFNsnma1unlZWe5zgS1/x4FsiJzRNVdwdGRoNf6kK1LZ0DpCB71+m9r3jWzI7NLdWlS/Odjn5WpG771MtrabcLIr5KGjV7HdpycbJpzY5LHoCNr08Dy/vvvN0ttJk2aJP37949+PfXUU9HH3HHHHTJlyhQ5/vjjZf/99zft3c8991z0/qysLNNOrpcaZJ566qly+umny3XXXRd9jFZuvvLKK6aqcvz48XLbbbfJQw89ZDaFAwAAAADQVrxmJuo8xdau8vTjkJGx7ds/Gd+8YMcP63WsSks1a/GGuCBuTN/4WYfffJ84VP14VWScXI+CSGBZHwrJkNIC3wtu7H4/ZbScl6Cd/K0l38nEgd0lUzZFA8tIy7xKNk/Tyhc15HQLT61N4+b77Ob7l0o3Xw3V+zWuljHdukmeNMqo0Pfyp6z5curhN5tFNaVm4Y37UaxZmQsr7jOXsa3d4aRhY6Jj249TX+5/ozs6Ho+639YRmTuQWH5+vtx7773my8uQIUPk1VdfTXgcDUU//fTTtM4TAAAAAIBtQZeqfL5mS/ztI/u0+fxKNx+uiN0xMaJ3kWQFRJrGVCZlPUzndXrZfVAPee5nu8t2170ec/v6JJvFrVmZVhiqLeFTdxskV772Zdxjc/SkwyKj+xbL9MkjTTu4s+r0zneXJXy9z1fH/9zStam6Ia4lXOdp6jzTZJ9lXnZQfjJ+gPzBNu/SGcQGsvNj5kwuDvYyrdsxHNffzRogz+zxYzNb0m3bdtmUp2Tj6/8nodrY34nkEoeNeuySiRdLxce3JzhGQHJK/c0bRcfULpbuAAAAAADQFc1a1LyPwe7puatbbfO4VvL5rbC02q4tv3vza99hpV+VdY3y4vy1cbfr6/g5z/8s+y7aEr7bIPcqSA0z60NhucolrPRbdbrKtkH9ioNGSEtsdqmw1Hma2ppu53ZOWmFpbUi3KlTH9SuJbhp3toTrPEkTViYpItPlOdd/NithsJg3YF8f7y71sLF6+esJn6+hp7amo/MisAQAAAAAoI14zSlcvqk67U3h1uZxrdzUSka91OvTZix0fbxW8rWnnctaSXnnux4boj3mW9ptaFqGU98YMuFnouN4LTdKVnWqp9DLtizomc9Wp7Q8SKsi7axZk/YZllZr+rNTd5Px/UvMfeP6l8gtR+zkOFaW5Oc0B51n7jlYPr3kgJggtnrlW3FzJrPEu8pVaai5eHNsu76dzqGsXjZDUuMvbIws3nGnW8/LpjxtWtPReRFYAgAAAADQRhLNKUx3U7jXdulbZy9xDUG1kk9DsaLcSOilcx9183Rb0e3bSxMsyxnco8CEd/qVKLtctblGTvr7x573J1pulKzqVMPMNRXNLeq63GdDpf+t4bWOlvj5a7fEtYTbfz4aQFbdfIS5nDyqT1z4aQ86C23hpaXik7vjbmsMxD8uRjgsfQviZ4layufcIKnKLh7sK2x0X7wTkNze48zWc8LKzo/AEgAAAACANqLVjV5S3RRutYG7zcT0CkGt55z6+CcSCkVqCu85dmx0cU0mOasHE0mwoFt65OeY8O6xU3Z1rYLUVm+rJdz63o19KU2qVac9C3Ji4rRMVajaW8L9Vmea8NYWUhY2Bc929Zub51uqu/P3MC3fCQUCsnxruTz3zbyUqyC9NGxZ7uvTal68Y33KtIF3NQSWAAAAAAC0Ea2ey8sKphSmudF2b6sNPBF7CGq1js9rah2vbqr6023bRbmZ39F7mKMyMJHGBGGa9R6sytB0gg2v7eAW69jZHsnp99X126SN3k9la67j98VPhWWOqVhstixYGr90x0VAAp5zLCNVkKlKvCHcudRH278DWXm0gXdBBJYAAAAAALShgT2aF6L4CdOcNHjUdu9kNJ6yh6DWYhln8Pb4J99G28NVblZAivPcA8zdBsYutSnJy5bu+e6PfXHBOnO/HwO7F7i/B0eQq8Gi741BTbJcltJ40SpNv/TctJ3emjeplymeWkylpN/AUqsy7VWXbhWWBUMOjbmum8LjKixdQuKwhD3nWEaqICWjG8KdoaW2fw89fwtt4F0QgSUAAAAAAG3IHjBpwOUnTLNvAdd2bj80jrKHoF+s2+paJbi8vDqmSq8wN1sO2aG36zEDjiq9E3cZIPUJ1oZX1MZuGU9ltqdXkJtq+/rAHgVxS2ncXPLSAt/HtM7t9qPGxMybLPEIb1vSNu9eYWn7eTlCT12OU/Hx7TG3XVDzv/hN4S4Vl1phOap7mWegWLLrxXHPUNnFQzx2miffEA4oAksAAAAAANpQTX3zApbtuucnDdOcrdz65VfYdgyv+Y7DexXGVVg65yZa1m6pibm+cWudVNW7b+ZOJiuo8VjE64s3ui7bcQtyd+jtvbjIzeqK2HP2sqK8Oulj9HzN9m6PkHmX7WIrUJP55+drkm6Hd/4sTGBpayV3BpqR5Tix4eFhDUvlF7VzHSFl7O9DpPo2LFdNiK3OtMsfsKfrUp1BZ34lZVOetB3J/4ZwQBFYAgAAAADQhmoamgO+REtikrVyJ6PZlLV0x2uTuLps0vCYwFK3ds9ctN41NFu5KTb8W7kpecjn5cQJA9yK/KLnrst2nIGghnsfrNiU0uvoSyQLBf0aXFoQraZ0C5l36uu9ZdvN1rpGE0YnOr9cZ2CZEzvDMuj4ECPLcZy/LWF5J3s7Rxu47XlhjSpFLt15khw7ZKzreWjl5voZJ3ou1WEOJVqCwBIAAAAAgHZSYVnno1py8YbKtBa+aDb1+ZoKE4bpMbycMH6AfF9VH3NbeXVsK7fXbMaPVm1O6Zzsx3nik2/FK6/Vc3fbmn7Ji/MlVdqyniwUVIMds0XdJJtR+W2aAa5zm3vClvCsoLz6RXOgPH3mlzHvLbIcJ/5MdfFOooRY75m12jvYdqvcdC7VYQ4l0kVgCQAAAABAG7K3dNc1hnzNd0x1mYtF80AN6/oW53keQ2cgfrgycdViKm3oTlZGZkYo2m9P8hy3rekrHBWeTmftNThuLmTYUW3q5bajd5Zk1m6p9bxPQ8OXFq6TdLiFs/bWefvycq1q/cnfP45eX7WpJiaQjSzHMe86+eIdG73Ha+FOospNv0t1gEQILAEAAAAAaC8t4QkW1limTx7lO+jzDAzD3i3l/a+Z2aJA0iknGDAbs3XG47NTdzPzHq25j3cePSb6OK/zSXVrut1rX26QRpeyTa+KTTvdQK7n67Xt2ytEtSRqu08m0XFVti2xfO3L9THn5wxkna3ZkqWVo4Ho4p1AuOln7QgvzVZ5j4U73pWbLNVBZhBYAgAAAADQRjRMs4eUWmEZTlD1ZgVpvzl4RPT69r0K5bx9hvp+TT38uq21JoxzW6azwdEO3hIanI3uWxyd8ajnbt+ire3MySTamq4zJBPR6kOdCxpIMWy0WOf7zNTdos/zG6LqFvZ0JTquVk7W2X5n9NtwkkDW3podMI8Oy2ENS+TeyldkVOg7yQ43RtrAm373NMTU7xIt3Imv3GSpDjKHwBIAAAAAgDZSa6uutDQkWbyjgdXfPloVvT5+QInc899vfL+mFdZpGNe7KFe2pUSVjPo+znluXsLnH7Nzv4Rb0287akzi17ddphI2elVb2qtDvUJUe+u2G/uto/vGhqa9i3KSHveSlxYkPd9EgWykMjJCQ8sZW/8hX1bc2xRebpTccIMJMe+rnCH7r3jc8zVYqoNtKXubHh0AAAAAgE5MQzdt/dUlNjpbUtu1Ndzy69nP4xe/6OKdHI/KQ309nU8Ye9ta36/nDOsqamKX6WRaouDMz7bzcf1LfAWJ2v6swWhtQ6Qy0K0tXSs99TGj+nST6ZNHJgwFvV4rlZ+tWyu608g+3WShrRLzwRPGJzwv/fkvL0+8yCdZIKuVkc7t3lZ4edjWJTG3VXx8u+T339OEk270dq/7gJagwhIAAAAAgDRY4eG8NVvMzEe99LN92v78nz051/V2L1bIly57ZWAoFJatdekFlidNGOC43j/l4MzPtvOCnKyk52JvMx/bv9i1/Xt0v+KYVvRUw8p07NS3m8uER5GivOb31KMgJ+b+otzE7zfRXEyt/PRT/WkCxmDs6yZi3/oNtBYCSwAAAAAA0uCsEPS7fdr5fKdb3vo64VzE5HV77vS1rrJVFlbWNTr3rEQfp3KyIt9pCDZ5ZJ+Yx7y77PuY65dOGhETvulTkwVnfrad5+ekFltYC4la0v6dKa7nIiIDSnTpTcQMxxbxbnmJG2E15PXy+Cm7+g5kc3ru6HtdE1u/0RYILAEAAAAASINbhaCf7dOJnq+WbKxKeS6i62MdD9XXsleAbql1r67Ux102abjU3jJFQrceaUKwHfoUxTxm9eaamOtFudlSbKscvPiA4UmDM7dAz0nD0lSkM2tyW3E7F/1c7aHjxsq6mOd0y00cWHqFvENLC1J6j/ELc7zllI7yfVwgUwgsAQAAAABIQ9/ivLjb/G6fThQ+6SKcCbfNlsLLXzGX9hZxr7mI1nGyAgEZ3z8S0o3pF98erX786EfmuP/0aD3X9zBr0YaY215eEDsn03kW3fKyYsK2kvzstAK9E8b1T7kl3O24rd3+7fdcZi5an/DxyVrCrZDX6cfjY1v0k3EuzJGs5qpPpx4m3ARaF4ElAAAAAKDT0ZDPK/TL1PHdlp+k0n7sFT59W1HjORdT5yK6sdqxrzt8VDSk86rg1Nv0uL96Yb7rsdyqRL+tqE34Xt76amNMO3NJfk5agd7EgT1i7s/PTj2wbM8StXT7aQnXz+vSScNjbtNQ+g+zl6T8O66h5XanfiRDz98iAa9BA8FsKRpxTErHBTKBwBIAAAAA0CWW4UybsTBjIabX/MlUWnM1fDp77yHme+30zra1e8fMxZTmuZgacrqpqW80l/e99030fSWaEZloDqazSlSPl2zj9elPzpXqpnNQxUmCN78VhqnOsGzv+nbLbVGFpZrlqNJMdXaqm+xSDdnjVwTl9hyd9jGBluhcf/kAAAAAgC7PbRmOunX2krQ3ejt5VS+u3VKbtNLTftsL8yOt1qfuOtC1xdw6/4XrtkRDzqtdKjirG0LR2ZLW+4rOiEzxvTmrRBNtprazztH5fSq+WB/7vI9XbZZOxW1Qp80+9/wn6e+kW5VmKrNT/c20jPwF0Q6OtkJgCQAAAADoVLzCRGnBRm8nr+pFe+joVelpv80KOL+rqpPcLH//ib7nkFLP++zvy5oRuaPPmZoW55Ia3Uzuh70IU8NhrWhNhX5e97+3POa2619fnPF2/ra0zhFoO833EaS7/e6lMjvVz0xLvSyb8jTt4GgzBJYAAAAAgE4lUSt0pqrSvOZP6lzLvGkzJHjpy2a5jXkd6/Xsr+143sxFG6S2obml2qk+FI4GgPWNkWpKP+9LQ8t/n/MD8Uvb0sMt2Exup6FlKmGjW5u9vR2+K/xu+gnS3barpzI71c9MS71kdiXaEoElAAAAAKBT8QoT3aRblaZB4OAeBZ7hovJ7DqohFJbVSRbbWAFgXZLA0llt93qSzdTO83BW+CWbX5lIKmGjW2WsXm9Jq3N74wwb0wnS3barO6tigY6OwBIAAAAA0Kk2f2ugc9MPd/R1zJZUpa3bmjhg3BY0AKxvTBwgOqvtdIO0G6/CSWeFn9dmcj9SCRtdW51bECq3R86wMcflh+Cnvdu5XZ2wEp0NgSUAAAAAoN3zmgfpFVruNbR5zmNulnsypzdfO2tR2lvDt+9ZKK1NA8BEFZb6Tp3Vdos3xi9pUV6Fk84KP2szub0F2XqtRFING90qY/X65JF9pDOxwsbHTtk1Wo1rl4n2bqCjI7AEAAAAALT7Skq3zd+JZv1pqGlp1ATIhRYqft6CreH/t/eQFN9ZJEw85wepP88eACaqsNy5f3FctV2/brmpvY6jws+tBfmyScMTtjZbP6tUgjd9nYsPGBZ3HK0Q7UyLdxLN7FRDSwuomESXl93lPwEAAAAAQLurpLQCLytI1NbZcAqz/mrqmwPLgd0LzDKcRKxjW9u1/dhzcOy2bj1Ht4o5O63o3HtoT0mVPQC0Nou7udolIKyyfRaex29a3OK1wEU/E+fnotvK9fPSn8GoPt1k8qg+MmvRhuj16ZNHphy8vbF4Y8Kt511hm32iny/QVRBYAgAAAEArsSoFNajQeX3aAtvZQpiW8qqk1E3VuhDGGfD0Lc5zPU51ffPG7Smj+8q9//3G1+svXLfF989xgeOxw3oVylceIZRFA1it6kzVzv2K5ZrDRpkA8O53l3o/0FHyqOe6obIu4bF7F+bKdt3zUw4a3ULMW6ZIi3yxbmtGt7m3Z/rPAP19CKc4vxLoCmgJBwAAAIB2OIOxq3LdFB2ObKp2CwK1ctLtM7S3hGsId/AOvX29vgajiUybsdD83DR0dI6S1HPPy078n9kmgHW5Pdk8yHrb+69L0BLubJHXYDUZnYl51eSRbb7ARX+ObhWqnW3xjtfGcK/qVqArIrAEAAAAgFaQ6gzGzkIDPp1FGbz0ZXOp15NVnTnp5zS6X7EU52W53uf2GdbYKiwveGG+vPV1bKuxFw1GEwVqt3ps3LYk6Qg33B6S7Glfrt8aaY2fNkNuf9v7HJyViBqiJlNR29AuwnOvcDXVWZgdhdtsUOfCJKCroiUcAAAAANqwcjATra7ttdVcw0l7wKdVj9b1308Z7focPXcNz5yf0/w1FWZJjvj8DJ/5bHXKQaLSYNSLn2rF+gQbvBOxh9nJAtVEMw6dlYhubcde2npOpFe4qrNBO2uI59ZWD4AKSwAAAABoFRocOdt+/c6rc9ua3RFaze/5z7KUblca3hw0IrZ9Wz+3BF3Qrp/hu8u+l3QkquRzm6/o5DMXdX1esrZwN4Ek5+9sO27p/M62+BtJFCID6JxoCQcAAACAVmAFR87qwMkj+yR8XrJAMhOt5okC0Zawz5H0c7slJyuQUgjoFjLqgp5UDCjJT9qOm2y+ZUvl56T2n+j66N5FudHreVnBuM/K3nac7Oy39ftLhpmOACwElgAAAADQCjQ4+sWeg2Nu03joD7OXJAwIrTZkeyCprEBSq/5a0mq+LSs0dS5fKrdb5zNz0QbfrzG0tMA1ZHRknkmd/YMhSduOE823zITq+tTayfNygjEbwGsbQ64/O/3d02U6z0zdrU3fXzLMdARgIbAEAAAAgFby8sJ1Mdf9VEN6tSFr+24mtipvy2VA5+07zPX2Czxut84nFbcdNcb19nEDSlI6zubqhqSP2alvyzdV79wvc9uuaxtCrlWTl7y4IGEgqDMh3bSH1msrXG3rjeUA2haBJQAAAABkSLJZk27LUpJVQ3q16ertmdiqvC2XAelinR1tW7+16nHapOFys8fCHet8/Dp5lwGegdZug3qkdK6ba+p9tSy31Oi+yVuz/dKs2q0mcvmmas8KWQ0E/3HaRPO9NdfSuuyMm7gBdEwElgAAAACQAVZr9edNrdWfu8ya9JKoGtKtgtJq300U7oV9hqtapSdpLgMSH6+xanNN9PoPhvZMGFZai1f8+senq004rNvIna/r3BKezObq5IGlhn1l3ZpnRqbi6DF9zeXTn61OezGPU3aCmZOJKmRpvQbQ3mW39QkAAAAAQGdwyYvzPW5fYAKiROGiV2WbBm9ecwW1fTccDptg1Cuw0tf1Oq6GqfZWcLdlQMNueF1WbIoEjoNLC0z7tdcxvV7Dublbw8VZi9abz0PDSa1atB9Trzufl4iGw7fOXhKt6HR7XT/+OW+Neb+a1q7bUmvObfKoMnlm7rcxn8F3tpmRqZizolwybb9hPeWtJd+53pesQlY/c78/SwBobQSWAAAAAOCThmFaKWmFbRpoWeGb1+brFZuqzaU+3i1c9Foak6wqU0NODRu9wjl7YOU87801DZ5hpbps0nCzDMhueXm1eS2dgegn6HLOxrRouGjdbi34cR5Td/JYH2duVkDqGpPXJN7zn2UmsPR6XYvXfZoLL28KJpX+rJw/L/0M0rVuS+Kgc3z/Epk8qo88PXd19HdGA9KfjB8Q97OwHDeuvyz9viruvDJVIQsAXbIl/J133pEjjzxSBgwYIIFAQF544YWY+/V/LZw+fbr0799fCgoK5JBDDpGvvvoq5jHff/+9nHLKKVJSUiI9evSQM888U7Zujf1fkj7//HPZb7/9JD8/XwYNGiS///3vW+X9AQAAAOg8tDLQ2fKt4Zu1XTvd+YcanrnNvFReVZm6NCXRMhL70h23LeAacCWKAGcuWu95n99lPG6zMS3Ojecn//1j8xlohaOeq/3j9BNWKutnkOh19XPZrnu+tCcaLo4fUGIWzNwyZbQsu/IQabz1SPO17LeHmNt65LvXGuVmBaNLh+zzKLVClnmUADqyNg0sKysrZfz48XLvvfe63q/B4t133y0PPPCAfPDBB1JUVCSHHXaY1NQ0/69eGlYuWLBAXn/9dZkxY4YJQc8666zo/RUVFTJ58mQZMmSIfPzxx/KHP/xBrrnmGvnTn/7UKu8RAAAAQNsvvkm0DMfvMa22Y6dkcdqQ0gJzqRWEew+JXwSzorw6GiTaZ14qrYYMJNjm7GfpjtsW8GQSta/7Xcbjde5eczr1M7BXOKYqX8syk7zuLtuVxMzUbA/8hIta4OMmJyvIPEoAnVIgrGWM7YD+A/j555+XY445xlzX09LKy0suuUQuvfRSc9vmzZulb9++8sgjj8hJJ50kX3zxhYwePVo+/PBD2W233cxjXnvtNfnRj34kq1atMs+///775be//a2sXbtWcnMjw5Evv/xyU8355Zdf+jo3DT27d+9uXl8rOQEAAAC0T87ZjPagztkKPCSFmYwacnrNikzmn1N3i1ZDHvan9+X1xRuj9znPSXOpcf0i1Xb29+N2TH3ejx/9yDWA1ArM2t9PMd9rSOunAtSuT1GubPCY1WiqAS+OnF8i6c6STJe1fTzR6+qOGv0v4HbxH8FNP39th09ULavyfz3DtdL0V/sNkzuO3nkbniEAZE4q+Vq73RK+bNkyEzJqG7hF39See+4p77//vrmul9oGboWVSh8fDAZNRab1mP333z8aViqt0ly0aJGUl7sPPa6trTUfov0LAAAAQPuXqJrQGfdYMxkTVVtalZnphpXO+ZSbqxti7neek4Zp9gpGa5uz3fj+xfL+8nJz7l7Bm1WBqfoW56V83l5hpfLbaqznfs+x2z5Mywo0h5X2z8xtgXZoG4SVgaaAOB3jBpQkDSv1d9CrLf6ud5fFbUgHgM6g3QaWGlYqrai00+vWfXpZVlYWc392drb07Nkz5jFux7C/htNNN91kwlHrS+deAgAAAGj/Es0vdKMVjV4zGe2zH9NlzRe0bKqpT3o+zmUpR46O/e+ZWttWbC+64dtqgV+dwRboZLMznfYe2lO2taPG9IuGlZajx/Qz4WSqUokdrS5tDUf/cdpEzzBVW9X1Mt3wN9HiJaW/C6mOOACA9o4t4S6uuOIKufjii6PXtcKS0BIAAADY9pzbrHVRjZ+WbYs+RwNGv1mVs6LRLtm26WRO3XW7mHBP39uS7yKzId2Oa24Li2yqrjdBo/X+D9mhd8zjvkmyqVrbub22SrdEwFG56UdFkoC2JedifX4vzF9rwln7xvbtexWmddzc7KAJhJPRgsqx/Upk+uSR0Z+xBpcafuvv06g+3WLuU3/5YLn84pnPY45z7axF5n0k+h1PNE/Uoq+byt8JALR37bbCsl+/fuZy3bp1Mbfrdes+vVy/PnZ7XUNDg9kcbn+M2zHsr+GUl5dneuntXwAAAAC2Lbdt1m4t24kW6GjAl2rA6KxotF4jleDTzbBeRTHH0/fS2JSFuR03bGtVt7aQ63OueOWLmMclm0dZXu3dzt0S9kU+fm2pbTSXw3sVRpfipNk9beRkBUyV5+AeBTHn5dzYvnCdv8VATn7CSlVakCNXOQJJDQx19mjVzUeYS2cl6kkTtos7jtfveKrLi/wuQgKAjqLdBpbDhg0zgeKbb74ZU+mosyn33ntvc10vN23aZLZ/W/79739LKBQysy6tx+jm8Pr65v9lTzeKjxo1SkpLS1v1PQEAAABIbf6ks2U7WaipodGlB2yf8pxJO+s1WjrrsLo+EtbZ31s67n9/eUqPT3G/jm9a6akVgX42rVuh8vGPfGiuF+ZmmapD5bdVOzcrGBNuHju2n9TeMsUsE+pekO36eSY7dAuy0hjfVdUnDRqd9DNwcvsdd/ITwruF7gDQkbVpS/jWrVvl66+/jlm0M3fuXDODcvDgwXLhhRfKDTfcIDvssIMJMK+66iqz+dvaJL7TTjvJ4YcfLr/4xS/kgQceMKHkeeedZzaI6+PUT3/6U7n22mvlzDPPlF//+tcyf/58ueuuu+SOO+5os/cNAAAAwN/8SWfLdqJQ02qJfXLu6pQ+3hcXrDPBk/X8lraCW6rqGtOerdkevfFV83Zzq/rzqDF95f1l38uGqkiBiM5q1KCx2pGapjMHtCEUku2658vKTZEZnLsP6tHiz1Nbvg8f1cf8zFvK+XuX/PGBlMcS2JcI6WvNW1MhIY+ZpQDQmbRpheVHH30ku+yyi/lSOjdSv58+fbq5Pm3aNDn//PPlrLPOkt13390EnK+99prk5+dHj/H444/LjjvuKAcffLD86Ec/kn333Vf+9Kc/Re/XpTmzZs0yYejEiRPlkksuMcfXYwIAAABoP9y2WTuX0CQLNTV4XJXGkhl7hVumwsUqW4Wln7ZeaaXqwEx6acG6aFipdJm1M6xMl/5c7T+IkrycFn+edQ2hjISV1vml2orttk3cbdGSk9VuvnN/9xmisxZtSOk8AKC9a9MKy0mTJknY/FvI+3+Buu6668yXF63GfOKJJxK+zrhx4+Tdd99t0bkCAAAA2HY0aNTZjU76nwvWxutEy0eswCfZRmUv9sAzU2psgaW29WpFYkt09ApNL5rhubWJ600rbeFzSX52iz/PcCuE7F7cfrc0rNTfcb+zQb3+BphhCaCzabczLAEAAAB0HV4zHkvyss3G68+bZlZ6LZyxWmL9bFR2CjQFntbsymRLbdKpsNQKud8cPCIjx+1sEtSwxLjqtS9jZ5VOGi5tzW+Vp/W7Ve9IZnV50D+n7ha3oMeLW2WpnwpNAOhoCCwBAAAAtDmvNuyK2gZfz7daYjXQSYU1q1IDz1Mf/0Qy6Zvvq2K2mdtnWiL1qketwLUvunlm7rct+hg9RkqmZO2W2rQDeb3eIz/Hd1hpX8BjnXuqFZoA0FEQWAIAAABocy2d8Wi1xE4eVZbS83KyAnL0mL6mijNTlZXFeZHWZa0KtSpD9fLOd5e163mUHcUlLy0wlyualvH4YQ/41GWThsu4fiWuMyVT4bey0XX2ahqt3NYCHj33/OyguUylQhMAOoo2nWEJAAAAAJmY8Wi1dN86e0lKz6trDGdsCYtlS5Kq0KLcLPO1fmtdRl+3q1jhMus0kSE9CqRHQY4JB0f16SbTJ480Ad8tUyL3T5uxMOXfG4vfykYN5HVTethlFEGqNLT0u5kcADoqKiwBAAAAtDmrciw7zYq3TdX18uMWLrVpLZV1jRkPK8cPKDGfXw/bYprObnBpga/HrdtaazZsV918hLl0ViP+fsrotOZhTps03HdlY7SV23abXqeVGwDcEVgCAAAAaDehZdjvBhaX+YaddYu2Hxp86ee37/a90np+uo3R3XKzZFsZUOK+gXtIU1B521FjMrbJW0NLDXzH94+0WmtVpr6Ofq+3aQu5dZ9eahv2zVNGpxzID+yeH73t9iPH0MoNAB66zv/8BgAAAKBNacu2Lh/ReX7aIqtVZ/bW1n9+tloaU0wdc7MCpq27K9M5jFrpp5/vjIXptbeP619iWqZrG0IpBb9bM7hISItr7Uu0gx5bcayg0goBf/aPTxOeh4bZ+tkka6NO1mpttZCnS4/9yapN8rs3vzbX//TBchncs4D2bgBwQYUlAAAAgDga8Ng3XFubmdN9jn6vMyrnNS2h0Uv7xme9/PHfP075J9HVw0rN9Eb3KzbfX/Li/LSPc9XkkaZlemz/yLHaws79SmKuf7s5slTHXunoXDCjIeAhI/sk/Yyun7VY2pr+jlthpVq0fmvM3wAAoBmBJQAAAIAYVrho33CdLFhJ9hytrNR6OStetC4veXFBzP3bgnNDtG4FT6eK0WpFbi/0/WgHvTUHMZWt2U5WoKdVr4mks1VbPzdtqU7m8zUVMdfNzMeASI/8HM/5k/r79cL8tQmPq59Rqtu4twXn73i4HYWpANDe0BIOAAAAIIZXpZ6Gi1bLrLO9e01FretzTv77x5IVDHi2Gi/fFGnX1eNkulZSF9FcdehIEwjZN0RfO2tRysd68rSJJiwbduMbpsW4LWm1obJvvG4pK9DTn2+folzZUBm/FGhoaYGU5GfHbbtOJCsgsuy3h5jv9xxSGv1ZKA22k0kWNl7yUiTwTkRDwXS2cWea2+94ewlTAaC9IbAEAAAAujC3uZJelXorNlXHVFNatJrSS30obL4S0RBLXzuVIMwPrTw81mUu4SmPf5LScTSos0JBnZ9of+8toZWH67bUmuBx8qg+MmvRBl9zJB8/ZVfXkFK3ZqcTpjoDvftPGOf6HvW962fn92ek1YQ79y9xnRGpYwP8ShQ2rkjyfp1VqG3J7Xe8vYSpANDe0BIOAAAAdFHTZix0beNOFkhpwJlJGtJpUJrpCstwguAoEatt12oht2+jtha92DdGp9oqrhWMOotRKw+tVudbpow2l8nmSB4zpq9nRaXfrdnJAj2392jNjkz22cUctyk0duP3OCrdsFHPfVy/+LmXbcX6HbePKGgvYSoAtDdUWAIAACCjm57RcX6Ot85ektJzrGBOf/aZZFWYleRlS0VtQ8aOe+rjn8hjp+wa9/upv7NuFYQaJP5s90HRSkevlmvnNmmr4tQKoLz4Dc68zk/DyufO2MPzeVbQaG+Bn79uizS6VLhqZpaXHfT9HpOdW6rt6pNHlSWszHWrbnUzuEe+LHepCNbnLW1qRW8v3H4+mWrpB4DOJhAOJ/pXKlRFRYV0795dNm/eLCUlsZvrAAAAupJoMGMtjGi61P8IJ7Rs3crIe/6zzFRFakB03r7D5PdTRqd0DN3i7Scwcmth9jt/0K+C7KBUZ/B4Tm6/n/q7nMngyDqeLo5x+w+sVAO0TJ2f/pzd2pDH9S+RTy8+QNKRc9nL4rWc3W8om+z3zwp/kx3POZ4g1fMAALTPfI3AMsMfKAAAQGfmGn5IU/hxSXrhR1elQYsut7HmRer8QW3pTRb8aljpVhl56aThKYWWOkMwk6Fja9AKw2XfV0dDPK9wUJzhXL/W+/10Vlv6Dd460vl4/e7oBvHa309p0TEs2obuN6TNdPgMAGj7fI2WcAAAAPj2xbqt8VtuRWThutQq9bp6O7xb6KjLUjRYSlatetc7S11v1+PNWrTe1znp+3BrE26PtILULYTyqqyTNt7C3N7afrfF+WTid0f/frwqLHW7eyrVn17t6wCAjovAEgAAoAvPgXQ7D+V1blnBQNKNz531s3W2w2ulqZ+A0VlR6TZvz06DJed8ROv9FOdmJfz8raU5iaot/QZ97SWs1CU0bvSz9KMttjC3twAt0+ezU99urpXWo/t5LwtKZRYmS2gAALSE+0BLOAAAaO05kOm2C6cS4CUKrrzOLW/aDM/ArD3MsfR6T6m2S7sdVxe4OFtYk7UbW5+9Vqb6DXqzAiJj+hWbn1ffbrkm4LR+Dqnw+nkMu/ENU83ZESRqMc669OXk7eBNnxvzDNtnm3nkn3MLZMWm6ug/524/agzt3ADQSTHDsg0/UAAAgHTmQKohPQpk2ZWHJAwSUw0Fna3H9gBSgzQ/S1fsoVyisGt8O5hjOeyG1z0rGNMNVJNVJHpVATqD6VSk8xy3Y4ztXxxXYeon6GsvErUG+30fl00aLre0IKyGO+ZGAgBSxQxLAACAdkwr59yCluWbqqMVeX7bhRPRYznnJFqvq1VN67ZGtj37nQGox0tUmffZmgpTgalt4zrjTttGU23Hbmk7t1WR6ubkv38s/zhtYsqh5SUvLUh4f3Ge+5QlfR/pBo+ZCBTDthZx1acoV+4/YZx0JIlag7UaL1mlqIbtsxZtkFv87YFBB257BwB0LsG2PgEAAICuRoO4RIGkhnVeUlkekij41HDUK2hz07c4LxrAJaJtz9o2rZdWWKYhpB9WRaI+T49hPV+rRO2P0QpV3TCsl36PbZ2b1/l4HTdZSKs2VNaZxzmPscBlQVFb0vPU95/Kz72lAk2Vt9oqrG35Wo3qhz4uWXuxjkhobwt3AABAZjDD0gdawgEAQEvZZ1KGk8zs08pEr1btIaUF0j0/21cFogZnzpmL6dLqvI2VdWkFcH0Kc2XddYclfVzfq2eaUM3rcxlQkhczz9He3q78trhbrfd+Zor6PabOnWxsT+lkO+EVOupn/uNHP/L8fUq0bCeVeZxmnEH/1DZOAwCAts/XqLAEAADYxrRCUAMxDdvCPqoAJ48q87xfwxlnBaK2YbtVGyaq5EyVBonp5nEbqurkmIf/l/Axeu5eYaX1uVizKa3zsMJFbW+3KjP9sFrvnS3f9uOqVI7ZGcLKTP+HwbRJwz0rJDVkzw561+v63eptVVlqMOlkLYJh4zQAAB0PFZY+UGEJAEDX05JZivbnWlue/dLcRSvCrpo8MmEFWqJKyC21DeacNfh0zrBsS4k2dWvg6jccdJPqrEirNTnVn09nZVU0tmSDuP4M8rKDMqqPzi4dmXTTc6KfeSrbpu3LX/p2yzMnsm5Lre/zAAAArYMt4W34gQIAgI7Tmm0t7tAqLXsY6bUV2r60xCvMTLZR2q9x/YtbFOC1V9rSrmGSFajOWrTefI61DaF2Ne+xtejvVKLK0tZgQvKmbdzR9vim6sRUaNt+7e/9b7fx+lvRysyb2eoNAECnQ2DZhh8oAABovxKFiTqv0Aod/VT7uc071Oe3pEINXYsV8AUvfbmtTyWmotFesZjKDNTxTaFnKuyvRUUkAACdW0UK+VrrrQgEAABo4xbuRFuzNTSxHp9oS7fFOe/w5L9/LFnBQMaW3KDz098XNaRHftpt6ceM6SvLvq+W+WsrWjRH0942rX8H1t+Cn8VNVmifzqxI+2sBAABYCCwBAECnq5y0ltHozER1z3+WJQ1dtMLLooFnqu3YuhRGvwC/Gpt+X247eueUxggEmkYZ3H7UmGjQ2JIZoN6rb0TO23eY6xxUKyilMhIAAGwLBJYAAKBNF9RkglflZCoLZ4rzsk3oo+8hUYCDjjObsb0b3a/YXOrfiobrfn5f9Xez8dYj4273UxWcaK6oF2tJkhX663KeC/YdxoxJAACwTRFYAgDQhWyLYNGrutE+EzLd5Td+LVjXXB2ZLg3XCNgyQ0MtXU6UieVDnZm9hVqDwb2GlKY1OzJZVXCy8Fj/7hLRc/Pa7g4AALAtBMLhVPf/dT0s3QGAzlOJ15VNm7HQtYJLK7taEkb0vXqmaxiiVVvLfnuIZ1DpNbNPF5Foa7WGXtqO6nVuyY4D/6wZhJlibXn2+p3rqHRz9rj+JXLoyD4tfl/JNmEPu+F119/toaUFstTj78pr4/YeQ0o9w+NUN3sDAACkiy3hGUZgCQCZ4fUf1C0NzDqrTIS71jG+WLc14XzFZNWQiY6fqIpuXP9ic94q3XCxJC9b/nrSBHN+ft8P/NMArCQ/O+X5hzlZAblov+0llKBdWFvs563ZktEwtK3b061t2tZ268/WVPh+roaDo/vq38TImCU3qfxt2bd5p7Jx+5iH/ycvLViXcnAKAACQKQSWGUZgCaAzSqcdt6UBWqKlEOkGZpk+x0xwnsPkUWXyzNxvE37WzucM7VnoGi4kC3ftx+nbLTelgNBa5PHj8QNk1qL1np+h/TXqG0Mt2kyMltOfW+8WBHIagOmPMJX2ba8qPyc/G6a9wtAjdiyTF1z+BlKVrMLQLw1jHz9l17iwMG/aDN/hear/nEsUQKZDK16ZRQkAANoKgWUbfqAA0BEkqorz+g9qr+ccNaavvHDGHr5eN1F4MaRHgSy78pAWhY5eFUSJQgLnf8BrC7LOkUvl9e3hbyrZnbZMr9tSm3KwqPRcJ4/qI998X5U05MwE6zNMVlHZmQUDIu2tqNNebWcPt3T7tDNEswLpHvk5rgFY8NKX03rdRFLZXO1W6ZdOFaO+z7zsYNz7G3bjG7K8vFrS5fWeU6kiHd+/RD695IC0zwEAAKAjI7Bsww8UADqCRCGC139QJ3qO35buZOGFhmLKTzCqQeNd7yyNhjIF2UGp9ghDtQ0zKxiICx+9Ak77TD/rMtUgF53LMWP6yitfrM9YG/oQW3DYt1ueLN+UPEjLCoqEmn7FNXi8/agxCVuD9fdSZy7qtHLrMlHQmHXpy56hm7U1PdnrOvmZYan/zElWOZhK2Dh+QIl8evEBGav2tFrK1117mK/POtn/0FB18xFpnQMAAEBXytfYEg6gQ3KrimvPMxDTqRhMVLWn//GsG3hTOYbY2n0ThYYL123xDAW9aCBhhRJ6boW5WbJ6c40JCbXSa0BJnklMViUJZfQ/+rWKzY0Gi3o++nN2C0G8wkql569f1vZqnYlYUduQ8FzCjksrlNTw81f7bx/9fdOfKzov/X1+4IRxJkxLpVowGWfoF/lbXSArNlV7hoZPn+avqlHpPxs0ZE+lnVj/+eAWCvpt/3ajowUS0X9++6k41ErkdDZv2+k/e9Odp6m/A34/a68AWv/RNqqsWxqvDgAA0PWwJdwHKiyB9sWrKq6li1u2xexDPeY5z3wmG6rqo7clq9jTMO6Ot5f4mgtovWe310m3fdWqAOps233RdWSqGtJZqZeomtaq4q1tCCUNxPwsOcn07EI/0lnykkyyqkavash0264ThateVacaSm9smv+poe1PzAzXDS367J3//LT+ud+SzxIAAKCjoyW8DT9QANtWssCg9vdTPJ9nD/SsKjlrVuGCtVtiAkK3UNEt0FT2CkZdfKGBRbLqPZUVkIwsK9FW6UzPLbTeP9DR2Dc4u7XpWluatZI4WaDpFi7ZKyGdLdJegZg1q7S1gseWyHRQmqwq1W+A5/XzjI5u8NHy3tpBcFuEzgAAAO0ZgWUbfqBo+y3GbdlOnKkKvZYcx/rM7As8hvjY+pvKsVPZdGyFeoneT7Ln6EKSqvqQqYDxG6JpKKF26tvNbGhOt1IwKCLpTTwDkAoN8HOyguafy/r326MgR76vqksp1HdWLiYKjJIFaYlmFiZCSOX/f2TyU2ma6LPVpVMtrYQEAABA6yGwbMMPtDNLFqIlu99tFp7+B2pRbrZsaapGswdgif4jx9m+lUqI6dVOvNug7rJhS21M0GefVZcsrPNqn9VZeXWNoWjotqHpvL1mESZrd04USD76vxUxLcHJuG13dju+9T68qgYzVSkIoOvyag32u9RI28Cf87mt3s9xad3NnERVqQAAAOg6KlLI15hhmeEPtDNwm4XXURCcAYB/znl/VgWbn3ZpO61nHte/xFS8/WH2kriWaPOYJBuUEwWEzsCrOC9bqhsapb4xbKrkL9h3WEqVes7j2hek6P8ARJgGAAAAZB6BpYd7771X/vCHP8jatWtl/Pjx8sc//lH22CN5NUZnDyz9bgEGAKQvWWDXmvzM+4v8j1efy4aqOs9FTm7HcWuJ1qfYNyhX1TfGVMkTEAIAAACdXwUVlvGeeuopOf300+WBBx6QPffcU+6880555plnZNGiRVJWVpaxD7SjYQswgFToCIMBJfmmAk83Itc3hszcwbqGUMqzPvX5l+y/vewxpDSuyq0zhYnOhSv6Ms4g0I/LJg2Pm9enx0rWLh3I4OZjxYxGAAAAAOkgsHShIeXuu+8u99xzj7keCoVk0KBBcv7558vll1+esQ+0oym8/BWz4ABA++S2RMTPPL9Utn87q+YSSaVtN9HGdK95g86FWHq+1S7/jNKwU2fMulXwOW/zam/W8LUwNysuTEylJVo/u6xAwDw20PSencdMtrHYz88z0XISexu3fi6NobDZgs0CEgAAAADtCYGlQ11dnRQWFsqzzz4rxxxzTPT2qVOnyqZNm+TFF1+MeXxtba35sn+gGm52xsAyeOnLbX0KQJdnBYbWZmRdQpUo7HKbu+dckPTwSRPiQjyvjbp+QrOWzPVzhpCpzBv0OrdUF6KkUxXYWkEgm48BAAAAdAUVtITHWr16tWy33Xby3nvvyd577x29fdq0afL222/LBx98EPP4a665Rq699tq4D7YzBpZUWKKjsoIvq51Yq/rCPqsFR/QqlOXl1dEKOg34SgtzZPXmyGb0ZJV1OVkBGdKjQL7+rirpeVrBmlfwlqhybluHgR1liy8tyAAAAADQ8RFYtjCw7EoVlm01w9IZGCWTGwxI3TZYCqRBVWV9gzQ6Ok4LsoNSFwrF3Z7KcZVbK6zVijq0Z4F8uHLzNn3PblVx+jO/ffYSX/MG9Tx/MLRUZixcJ43hxO/PrdU4Weh30X7bR8M1r0Ud9ll/zuf4qYxTVruu3xDOb3hnP2c/i0QI3gAAAAAAXVUFFZYtawlvyQfambaEawvkkTuVyaffVsTMpFMbmkIZK7yqbmiU+sawa4WXnwow5zZat2DK7ThaXaeB0fy1FTGBmgZtD5wwrl1UhyWSLMDy+9mlUxnn/Lln4jNzBniaEvqd5QcAAAAAADovAkuPpTt77LGH/PGPf4wu3Rk8eLCcd955XXrpDgAAAAAAALCtpZKvRfo6u4CLL77YVFTutttuJri88847pbKyUs4444y2PjUAAAAAAAAAXS2wPPHEE2XDhg0yffp0Wbt2rUyYMEFee+016du3b1ufGgAAAAAAAIAmgXA4nPlNJp0MLeEAAAAAAABA6+RrwRa8DgAAAAAAAABkFIElAAAAAAAAgHaDwBIAAAAAAABAu0FgCQAAAAAAAKDdILAEAAAAAAAA0G5kt/UJdATWInXdZgQAAAAAAAAgNVauZuVsiRBY+rBlyxZzOWjQoBR/FAAAAAAAAADsOVv37t0lkUDYT6zZxYVCIVm9erUUFxdLIBCQzppyayC7cuVKKSkpaevTAbok/g4B/gaBrox/DwL8DQJdXWf/d2E4HDZh5YABAyQYTDylkgpLH/RDHDhwoHQF+gfRGf8ogI6Ev0OAv0GgK+PfgwB/g0BXV9KJs5lklZUWlu4AAAAAAAAAaDcILAEAAAAAAAC0GwSWMPLy8uTqq682lwDaBn+HQNvibxDgbxDoyvj3IND2+DtsxtIdAAAAAAAAAO0GFZYAAAAAAAAA2g0CSwAAAAAAAADtBoElAAAAAAAAgHaDwBIAAAAAAABAu0FgCQAAAAAAAKDdILDsJG666SbZfffdpbi4WMrKyuSYY46RRYsWxTympqZGzj33XOnVq5d069ZNjj/+eFm3bl30/s8++0xOPvlkGTRokBQUFMhOO+0kd911V9xrzZ49W3bddVfJy8uTESNGyCOPPNIq7xFo71rr73DNmjXy05/+VEaOHCnBYFAuvPDCVnuPQHvWWn+Dzz33nBx66KHSp08fKSkpkb333ltmzpzZau8TaM9a6+/wP//5j+yzzz7mGPqYHXfcUe64445We59Ae9Wa/11o+e9//yvZ2dkyYcKEbfregI6itf4OZ8+eLYFAIO5r7dq10hkQWHYSb7/9tvllnzNnjrz++utSX18vkydPlsrKyuhjLrroInn55ZflmWeeMY9fvXq1HHfccdH7P/74Y/PH9Nhjj8mCBQvkt7/9rVxxxRVyzz33RB+zbNkyOeKII+TAAw+UuXPnmqDk5z//Of+hBrTi32Ftba0JSq688koZP348nz3Qyv8ufOedd0xg+eqrr5rH678TjzzySPn000/5WaDLa62/w6KiIjnvvPPM3+MXX3xh/p2oX3/605+6/M8AXVtr/Q1aNm3aJKeffrocfPDBrfYegfautf8OFy1aZIparC99XqcQRqe0fv36sP543377bXN906ZN4ZycnPAzzzwTfcwXX3xhHvP+++97HueXv/xl+MADD4xenzZtWnjMmDExjznxxBPDhx122DZ5H0BHtq3+Du0OOOCA8K9+9attcPZAx9caf4OW0aNHh6+99toMnj3QObTm3+Gxxx4bPvXUUzN49kDHt63/BvW/Ba+88srw1VdfHR4/fvw2ehdAx7at/g7feust85zy8vJwZ0SFZSe1efNmc9mzZ89oOq+p/iGHHBJ9jLbODB48WN5///2Ex7GOofSx9mOoww47LOExgK5qW/0dAmhff4OhUEi2bNnC3ynQhn+HWuH83nvvyQEHHMDPAWilv8GHH35Yli5dKldffTWfOdCG/y6cMGGC9O/f33QA6YiGziK7rU8Amaf/4aSt2jrXZ+eddza36QyD3Nxc6dGjR8xj+/bt6znfQP+fvqeeekpeeeWV6G36WH2O8xgVFRVSXV1tZisA2LZ/hwDa9t+FTrfeeqts3bpVfvKTn/CjAVr573DgwIGyYcMGaWhokGuuucaMKgKw7f8Gv/rqK7n88svl3XffNfMrAbT+32H//v3lgQcekN12282MDXvooYdk0qRJ8sEHH5i9Ix0d/2TphHRWwvz5880w8nTp848++mjzv5bprAUA/B0CHUlr/bvwiSeekGuvvVZefPHFzjMvCOhAf4caluj/YKBzwjQ80YWQuqQAwLb7G2xsbDQLIPXff7oEEkDb/Ltw1KhR5svygx/8QJYsWWKW0P3973/v8D8WAstORoePz5gxwwwg1//F2dKvXz+pq6szQ5HtKb5uodL77BYuXGiGJp911llmeLmdPta+uco6hm5JpboSaJ2/QwBt++9Cy5NPPmmquXRYunNcCtDVtdbf4bBhw8zl2LFjzTG0ypLAEti2f4M6BuWjjz4yoxj0dawqsnA4bKotZ82aJQcddBA/BnR5bfHfhXvssUeLwtH2hBmWnYT+y0H/GJ5//nn597//Hf1/3iwTJ06UnJwcefPNN2M2Sa1YsUL23nvv6G26fUq3nU6dOlVuvPHGuNfRx9qPoXTrlf0YQFfVWn+HANr+b/Af//iHnHHGGebyiCOO4EcCtIN/F2pgoi1xQFfWGn+DWqwyb948mTt3bvTr7LPPNpVe+v2ee+7ZCu8UaL/a8t+Fc+fONa3inUJbb/1BZpxzzjnh7t27h2fPnh1es2ZN9Kuqqir6mLPPPjs8ePDg8L///e/wRx99FN57773Nl2XevHnhPn36mO2K9mPoRivL0qVLw4WFheHLLrvMbLG69957w1lZWeHXXnuNHyW6vNb6O1Sffvqp+Zo4cWL4pz/9qfl+wYIFXf5ngK6ttf4GH3/88XB2drb5d6D9MbrxEejqWuvv8J577gm/9NJL4cWLF5uvhx56KFxcXBz+7W9/2+rvGeiq//+oHVvCgdb/O7zjjjvCL7zwQvirr74yj//Vr34VDgaD4TfeeKNT/DgILDsJzZ7dvh5++OHoY6qrq8O//OUvw6WlpSZ0PPbYY80vvP1fMm7HGDJkSMxrvfXWW+EJEyaEc3Nzw9tvv33MawBdWWv+Hfp5DNDVtNbf4AEHHOD6mKlTp7b6ewa66t/h3XffHR4zZox5fklJSXiXXXYJ33fffeHGxsZWf89AV/3/R+0ILIHW/zu85ZZbwsOHDw/n5+eHe/bsGZ40aZIJQDuLgP6ftq7yBAAAAAAAAADFDEsAAAAAAAAA7QaBJQAAAAAAAIB2g8ASAAAAAAAAQLtBYAkAAAAAAACg3SCwBAAAAAAAANBuEFgCAAAAAAAAaDcILAEAAAAAAAC0GwSWAAAAAAAAANoNAksAAAAAAAAA7QaBJQAAAAAAAIB2g8ASAAAAAAAAgLQX/x+WtBmjBirEHgAAAABJRU5ErkJggg==",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_pred = model.predict(fh=y_test.index, X=X_test)\n",
         "plot_series(y_train, y_test, y_pred, labels=[\"Treino\", \"Teste\", \"Previsão com ML\"])\n",
         "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -190,7 +566,358 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 7,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000500 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7642\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1618, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.495674\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-d7185d0e-6c8a-43bf-938c-55cf9eae5b03' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>TransformedTargetForecaster(steps=[Differencer(),\n",
+              "                                   ReductionForecaster(estimator=LGBMRegressor(random_state=42),\n",
+              "                                                       window_length=30)])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('c3f67d12-e171-46d8-9517-9cee1f9e753d') type=\"checkbox\" ><label for=UUID('c3f67d12-e171-46d8-9517-9cee1f9e753d') class='sk-toggleable__label sk-toggleable__label-arrow'>TransformedTargetForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.compose.TransformedTargetForecaster.html\">?<span>Documentation for TransformedTargetForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>TransformedTargetForecaster(steps=[Differencer(),\n",
+              "                                   ReductionForecaster(estimator=LGBMRegressor(random_state=42),\n",
+              "                                                       window_length=30)])</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('c4547689-69da-4e29-ab85-a5165a0a0d5b') type=\"checkbox\" ><label for=UUID('c4547689-69da-4e29-ab85-a5165a0a0d5b') class='sk-toggleable__label sk-toggleable__label-arrow'>Differencer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.difference.Differencer.html\">?<span>Documentation for Differencer</span></a></label><div class=\"sk-toggleable__content\"><pre>Differencer()</pre></div></div></div><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('2239e2cd-7870-44b2-8b54-3cd83c5d8c22') type=\"checkbox\" ><label for=UUID('2239e2cd-7870-44b2-8b54-3cd83c5d8c22') class='sk-toggleable__label sk-toggleable__label-arrow'>ReductionForecaster</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42), window_length=30)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('4ada77df-d282-46ba-902e-4f463e59d5f6') type=\"checkbox\" ><label for=UUID('4ada77df-d282-46ba-902e-4f463e59d5f6') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('a18915ba-370f-4752-b254-d9dd1e6d5ca8') type=\"checkbox\" ><label for=UUID('a18915ba-370f-4752-b254-d9dd1e6d5ca8') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42)</pre></div></div></div></div></div></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "TransformedTargetForecaster(steps=[Differencer(),\n",
+              "                                   ReductionForecaster(estimator=LGBMRegressor(random_state=42),\n",
+              "                                                       window_length=30)])"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.transformations.series.difference import Differencer\n",
         "\n",
@@ -203,13 +930,24 @@
         ")\n",
         "\n",
         "model.fit(y_train, X=X_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 8,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "y_pred_diff = model.predict(fh=y_test.index, X=X_test)\n",
         "\n",
@@ -217,9 +955,7 @@
         "    y_train, y_test, y_pred_diff, labels=[\"Treino\", \"Teste\", \"Previsão com ML + Diferença\"]\n",
         ")\n",
         "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -230,7 +966,41 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 9,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000492 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1618, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 0.002516\n"
+          ]
+        },
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from sktime.transformations.series.boxcox import LogTransformer\n",
         "\n",
@@ -244,9 +1014,7 @@
         "    y_pred_log_diff,\n",
         "    labels=[\"Treino\", \"Teste\", \"Previsão com ML + Log + Diferença\"],\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -259,7 +1027,41 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 10,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000441 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1618, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.043509\n"
+          ]
+        },
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "model = ReductionForecaster(\n",
         "    regressor,\n",
@@ -274,9 +1076,7 @@
         "plot_series(\n",
         "    y_train, y_test, y_pred_norm, labels=[\"Treino\", \"Teste\", \"Previsão com ML + Normalização\"]\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -289,7 +1089,76 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 11,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000493 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1618, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.043509\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000447 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1617, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.047248\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000480 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1616, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.050566\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000471 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1615, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.053004\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000380 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1614, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.055187\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000584 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1613, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.057470\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000436 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1612, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.060203\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000539 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1611, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.063325\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000467 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1610, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.066558\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000518 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1609, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.069541\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000446 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1608, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.072319\n",
+            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000473 seconds.\n",
+            "You can set `force_col_wise=true` to remove the overhead.\n",
+            "[LightGBM] [Info] Total Bins 7652\n",
+            "[LightGBM] [Info] Number of data points in the train set: 1607, number of used features: 31\n",
+            "[LightGBM] [Info] Start training from score 1.074788\n"
+          ]
+        }
+      ],
       "source": [
         "model = ReductionForecaster(\n",
         "    regressor,\n",
@@ -300,13 +1169,34 @@
         "\n",
         "model.fit(y_train, X=X_train)\n",
         "y_pred_norm_direct = model.predict(fh=y_test.index, X=X_test)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 12,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "(<Figure size 1600x400 with 1 Axes>, <Axes: ylabel='sales'>)"
+            ]
+          },
+          "execution_count": 12,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "plot_series(\n",
         "    y_train,\n",
@@ -314,9 +1204,7 @@
         "    y_pred_norm_direct,\n",
         "    labels=[\"Treino\", \"Teste\", \"Previsão com ML + Normalização\"],\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -327,7 +1215,72 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 13,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>MAPE</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>ML + Normalização + Direto</th>\n",
+              "      <td>0.136547</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ML + Normalização</th>\n",
+              "      <td>0.145583</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ML + Diferença</th>\n",
+              "      <td>0.164518</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ML + Log + Diferença</th>\n",
+              "      <td>0.174632</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ML</th>\n",
+              "      <td>0.202821</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                MAPE\n",
+              "ML + Normalização + Direto  0.136547\n",
+              "ML + Normalização           0.145583\n",
+              "ML + Diferença              0.164518\n",
+              "ML + Log + Diferença        0.174632\n",
+              "ML                          0.202821"
+            ]
+          },
+          "execution_count": 13,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.performance_metrics.forecasting import MeanAbsolutePercentageError\n",
         "\n",
@@ -356,19 +1309,28 @@
         "\n",
         "results = pd.DataFrame.from_dict(results, orient=\"index\", columns=[\"MAPE\"])\n",
         "results.sort_values(\"MAPE\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     }
   ],
   "metadata": {
     "kernelspec": {
-      "name": "python3",
+      "display_name": "tsbook-py3.11",
       "language": "python",
-      "display_name": "Python 3 (ipykernel)",
-      "path": "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/share/jupyter/kernels/python3"
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.11"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 4
-}
\ No newline at end of file
+}
diff --git a/notebooks/part2/03_panel_data.ipynb b/notebooks/part2/03_panel_data.ipynb
index 8f0ec19..4f2695e 100644
--- a/notebooks/part2/03_panel_data.ipynb
+++ b/notebooks/part2/03_panel_data.ipynb
@@ -22,41 +22,41 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 1,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# | echo: false\n",
         "import warnings\n",
         "\n",
         "warnings.filterwarnings(\"ignore\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 2,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# | code-fold: true\n",
         "import pandas as pd\n",
         "import matplotlib.pyplot as plt\n",
         "\n",
         "from sktime.utils.plotting import plot_series"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 3,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from tsbook.datasets.retail import SyntheticRetail\n",
         "dataset = SyntheticRetail(\"panel\")\n",
         "y_train, X_train, y_test, X_test = dataset.load(\n",
         "    \"y_train\", \"X_train\", \"y_test\", \"X_test\"\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -67,12 +67,117 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 4,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>promo</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>sku_id</th>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
+              "      <th>2020-01-01</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-02</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-03</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-04</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-05</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">24</th>\n",
+              "      <th>2024-07-01</th>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-02</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-03</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-04</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-05</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>41200 rows × 1 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                   promo\n",
+              "sku_id date             \n",
+              "0      2020-01-01    0.0\n",
+              "       2020-01-02    0.0\n",
+              "       2020-01-03    0.0\n",
+              "       2020-01-04    0.0\n",
+              "       2020-01-05    0.0\n",
+              "...                  ...\n",
+              "24     2024-07-01    1.0\n",
+              "       2024-07-02    0.0\n",
+              "       2024-07-03    0.0\n",
+              "       2024-07-04    0.0\n",
+              "       2024-07-05    0.0\n",
+              "\n",
+              "[41200 rows x 1 columns]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "display(X_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -84,16 +189,27 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 5,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1000x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "from sktime.utils.plotting import plot_series\n",
         "\n",
         "fig, ax = plt.subplots(figsize=(10, 4))\n",
         "y_train.unstack(level=0).droplevel(0, axis=1).iloc[:, [0,10]].plot(ax=ax, alpha=0.7)\n",
         "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -106,12 +222,30 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 6,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "PeriodIndex(['2020-01-01', '2020-01-02', '2020-01-03', '2020-01-04',\n",
+              "             '2020-01-05', '2020-01-06', '2020-01-07', '2020-01-08',\n",
+              "             '2020-01-09', '2020-01-10',\n",
+              "             ...\n",
+              "             '2024-06-26', '2024-06-27', '2024-06-28', '2024-06-29',\n",
+              "             '2024-06-30', '2024-07-01', '2024-07-02', '2024-07-03',\n",
+              "             '2024-07-04', '2024-07-05'],\n",
+              "            dtype='period[D]', name='date', length=41200)"
+            ]
+          },
+          "execution_count": 6,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_train.index.get_level_values(-1)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -122,12 +256,44 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 7,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "MultiIndex([( 0, '2020-01-01'),\n",
+              "            ( 0, '2020-01-02'),\n",
+              "            ( 0, '2020-01-03'),\n",
+              "            ( 0, '2020-01-04'),\n",
+              "            ( 0, '2020-01-05'),\n",
+              "            ( 0, '2020-01-06'),\n",
+              "            ( 0, '2020-01-07'),\n",
+              "            ( 0, '2020-01-08'),\n",
+              "            ( 0, '2020-01-09'),\n",
+              "            ( 0, '2020-01-10'),\n",
+              "            ...\n",
+              "            (24, '2024-06-26'),\n",
+              "            (24, '2024-06-27'),\n",
+              "            (24, '2024-06-28'),\n",
+              "            (24, '2024-06-29'),\n",
+              "            (24, '2024-06-30'),\n",
+              "            (24, '2024-07-01'),\n",
+              "            (24, '2024-07-02'),\n",
+              "            (24, '2024-07-03'),\n",
+              "            (24, '2024-07-04'),\n",
+              "            (24, '2024-07-05')],\n",
+              "           names=['sku_id', 'date'], length=41200)"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_train.index"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -138,12 +304,25 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 8,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+              "       18, 19, 20, 21, 22, 23, 24],\n",
+              "      dtype='int64', name='sku_id')"
+            ]
+          },
+          "execution_count": 8,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_train.index.get_level_values(0).unique()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -154,12 +333,113 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 9,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>sales</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2020-01-01</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-02</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-03</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-04</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-05</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-01</th>\n",
+              "      <td>220</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-02</th>\n",
+              "      <td>128</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-03</th>\n",
+              "      <td>47</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-04</th>\n",
+              "      <td>73</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-05</th>\n",
+              "      <td>165</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>1648 rows × 1 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            sales\n",
+              "date             \n",
+              "2020-01-01      0\n",
+              "2020-01-02      0\n",
+              "2020-01-03      0\n",
+              "2020-01-04      0\n",
+              "2020-01-05      0\n",
+              "...           ...\n",
+              "2024-07-01    220\n",
+              "2024-07-02    128\n",
+              "2024-07-03     47\n",
+              "2024-07-04     73\n",
+              "2024-07-05    165\n",
+              "\n",
+              "[1648 rows x 1 columns]"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_train.loc[0]"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -171,12 +451,118 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 10,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>sales</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>sku_id</th>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
+              "      <th>2020-01-01</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-02</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-03</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-04</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-05</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">2</th>\n",
+              "      <th>2024-07-01</th>\n",
+              "      <td>125</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-02</th>\n",
+              "      <td>185</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-03</th>\n",
+              "      <td>179</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-04</th>\n",
+              "      <td>210</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-05</th>\n",
+              "      <td>236</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>3296 rows × 1 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                   sales\n",
+              "sku_id date             \n",
+              "0      2020-01-01      0\n",
+              "       2020-01-02      0\n",
+              "       2020-01-03      0\n",
+              "       2020-01-04      0\n",
+              "       2020-01-05      0\n",
+              "...                  ...\n",
+              "2      2024-07-01    125\n",
+              "       2024-07-02    185\n",
+              "       2024-07-03    179\n",
+              "       2024-07-04    210\n",
+              "       2024-07-05    236\n",
+              "\n",
+              "[3296 rows x 1 columns]"
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_train.loc[pd.IndexSlice[[0,2], :]]"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -187,14 +573,32 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 11,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "PeriodIndex(['2024-07-06', '2024-07-07', '2024-07-08', '2024-07-09',\n",
+              "             '2024-07-10', '2024-07-11', '2024-07-12', '2024-07-13',\n",
+              "             '2024-07-14', '2024-07-15',\n",
+              "             ...\n",
+              "             '2024-12-23', '2024-12-24', '2024-12-25', '2024-12-26',\n",
+              "             '2024-12-27', '2024-12-28', '2024-12-29', '2024-12-30',\n",
+              "             '2024-12-31', '2025-01-01'],\n",
+              "            dtype='period[D]', name='date', length=180)"
+            ]
+          },
+          "execution_count": 11,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "fh = y_test.index.get_level_values(1).unique()\n",
         "\n",
         "fh"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -208,7 +612,115 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 12,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>sales</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>sku_id</th>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
+              "      <th>2024-07-06</th>\n",
+              "      <td>165.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-07</th>\n",
+              "      <td>165.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-08</th>\n",
+              "      <td>165.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-09</th>\n",
+              "      <td>165.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-10</th>\n",
+              "      <td>165.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">24</th>\n",
+              "      <th>2024-12-28</th>\n",
+              "      <td>209.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-29</th>\n",
+              "      <td>209.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-30</th>\n",
+              "      <td>209.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-31</th>\n",
+              "      <td>209.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2025-01-01</th>\n",
+              "      <td>209.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>4500 rows × 1 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                   sales\n",
+              "sku_id date             \n",
+              "0      2024-07-06  165.0\n",
+              "       2024-07-07  165.0\n",
+              "       2024-07-08  165.0\n",
+              "       2024-07-09  165.0\n",
+              "       2024-07-10  165.0\n",
+              "...                  ...\n",
+              "24     2024-12-28  209.0\n",
+              "       2024-12-29  209.0\n",
+              "       2024-12-30  209.0\n",
+              "       2024-12-31  209.0\n",
+              "       2025-01-01  209.0\n",
+              "\n",
+              "[4500 rows x 1 columns]"
+            ]
+          },
+          "execution_count": 12,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.forecasting.naive import NaiveForecaster\n",
         "\n",
@@ -218,9 +730,7 @@
         "y_pred_naive = naive_forecaster.predict(fh=fh)\n",
         "\n",
         "y_pred_naive"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -235,12 +745,75 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 13,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>forecasters</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>NaiveForecaster(window_length=1)</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>NaiveForecaster(window_length=1)</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>NaiveForecaster(window_length=1)</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>NaiveForecaster(window_length=1)</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>NaiveForecaster(window_length=1)</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                        forecasters\n",
+              "0  NaiveForecaster(window_length=1)\n",
+              "1  NaiveForecaster(window_length=1)\n",
+              "2  NaiveForecaster(window_length=1)\n",
+              "3  NaiveForecaster(window_length=1)\n",
+              "4  NaiveForecaster(window_length=1)"
+            ]
+          },
+          "execution_count": 13,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "naive_forecaster.forecasters_.head()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -261,23 +834,34 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 14,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from sktime.performance_metrics.forecasting import MeanSquaredScaledError\n",
         "\n",
         "metric = MeanSquaredScaledError(multilevel=\"uniform_average_time\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 15,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "np.float64(19.04893558607091)"
+            ]
+          },
+          "execution_count": 15,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "metric(y_true=y_test, y_pred=y_pred_naive, y_train=y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -305,7 +889,344 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 16,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-6f9e6b3e-3c10-4c6a-b095-da047497a4d6' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    window_length=30)</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('d050159f-e7dc-4546-a6c2-420d10c30e00') type=\"checkbox\" ><label for=UUID('d050159f-e7dc-4546-a6c2-420d10c30e00') class='sk-toggleable__label sk-toggleable__label-arrow'>ReductionForecaster</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    window_length=30)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('7dfca25d-a746-4df4-b747-c1fd7ee6355a') type=\"checkbox\" ><label for=UUID('7dfca25d-a746-4df4-b747-c1fd7ee6355a') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('5b9ea422-45aa-4e5a-a311-bd2c474bb500') type=\"checkbox\" ><label for=UUID('5b9ea422-45aa-4e5a-a311-bd2c474bb500') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    window_length=30)"
+            ]
+          },
+          "execution_count": 16,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from tsbook.forecasting.reduction import ReductionForecaster\n",
         "from lightgbm import LGBMRegressor\n",
@@ -316,22 +1237,33 @@
         ")\n",
         "\n",
         "global_forecaster1.fit(y_train, X_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 17,
       "metadata": {},
+      "outputs": [],
       "source": [
         "y_pred_global1 = global_forecaster1.predict(fh=fh, X=X_test)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 18,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
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+            "text/plain": [
+              "<Figure size 1000x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "fig, ax = plt.subplots(figsize=(10, 4))\n",
         "y_train.loc[10, \"sales\"].plot(ax=ax, label=\"Treino\")\n",
@@ -339,9 +1271,7 @@
         "y_pred_global1.loc[10, \"sales\"].plot(ax=ax, label=\"Global 1\")\n",
         "plt.legend()\n",
         "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -352,20 +1282,358 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 19,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-cfd9e29c-7fed-41cd-af38-68375b1d6516 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-cfd9e29c-7fed-41cd-af38-68375b1d6516' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ForecastByLevel(forecaster=ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                               window_length=30))</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('b14bfd72-41bb-4427-97cf-283f5bd05dd0') type=\"checkbox\" ><label for=UUID('b14bfd72-41bb-4427-97cf-283f5bd05dd0') class='sk-toggleable__label sk-toggleable__label-arrow'>ForecastByLevel<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.compose.ForecastByLevel.html\">?<span>Documentation for ForecastByLevel</span></a></label><div class=\"sk-toggleable__content\"><pre>ForecastByLevel(forecaster=ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                               window_length=30))</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('4dc7af08-6872-4026-aa48-f201953082aa') type=\"checkbox\" ><label for=UUID('4dc7af08-6872-4026-aa48-f201953082aa') class='sk-toggleable__label sk-toggleable__label-arrow'>forecaster: ReductionForecaster</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    window_length=30)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('f45f0702-c52f-4746-a5b2-be4459e9ca01') type=\"checkbox\" ><label for=UUID('f45f0702-c52f-4746-a5b2-be4459e9ca01') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('596ac0b6-a128-445e-a27a-0c67277b3432') type=\"checkbox\" ><label for=UUID('596ac0b6-a128-445e-a27a-0c67277b3432') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "ForecastByLevel(forecaster=ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                               window_length=30))"
+            ]
+          },
+          "execution_count": 19,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.forecasting.compose import ForecastByLevel\n",
         "\n",
         "local_forecaster1 = ForecastByLevel(global_forecaster1, groupby=\"local\")\n",
         "\n",
         "local_forecaster1.fit(y_train, X=X_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 20,
       "metadata": {},
+      "outputs": [],
       "source": [
         "y_pred_local1 = local_forecaster1.predict(fh=fh, X=X_test)\n",
         "\n",
@@ -379,9 +1647,7 @@
         "    },\n",
         "    index=[\"MSE\"],\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -394,25 +1660,364 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 21,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-3de84cbd-4107-4e17-9103-565769684975 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-3de84cbd-4107-4e17-9103-565769684975 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-3de84cbd-4107-4e17-9103-565769684975' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>TransformedTargetForecaster(steps=[Differencer(),\n",
+              "                                   ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                       window_length=30)])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('ebf7cd22-a333-4b6c-8176-71f14ce2a2a6') type=\"checkbox\" ><label for=UUID('ebf7cd22-a333-4b6c-8176-71f14ce2a2a6') class='sk-toggleable__label sk-toggleable__label-arrow'>TransformedTargetForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.compose.TransformedTargetForecaster.html\">?<span>Documentation for TransformedTargetForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>TransformedTargetForecaster(steps=[Differencer(),\n",
+              "                                   ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                       window_length=30)])</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('2d182255-af09-41a1-bd5b-ef518004f69b') type=\"checkbox\" ><label for=UUID('2d182255-af09-41a1-bd5b-ef518004f69b') class='sk-toggleable__label sk-toggleable__label-arrow'>Differencer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.difference.Differencer.html\">?<span>Documentation for Differencer</span></a></label><div class=\"sk-toggleable__content\"><pre>Differencer()</pre></div></div></div><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('c37e12dd-706b-4856-9b18-7fdcc5601fec') type=\"checkbox\" ><label for=UUID('c37e12dd-706b-4856-9b18-7fdcc5601fec') class='sk-toggleable__label sk-toggleable__label-arrow'>ReductionForecaster</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    window_length=30)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('c236b108-95f7-4ba3-a9b7-4af3e3f753c6') type=\"checkbox\" ><label for=UUID('c236b108-95f7-4ba3-a9b7-4af3e3f753c6') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('f550645d-a561-4c1e-a989-6f02884a1a7d') type=\"checkbox\" ><label for=UUID('f550645d-a561-4c1e-a989-6f02884a1a7d') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div></div></div></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "TransformedTargetForecaster(steps=[Differencer(),\n",
+              "                                   ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                       window_length=30)])"
+            ]
+          },
+          "execution_count": 21,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.transformations.series.difference import Differencer\n",
         "\n",
         "global_forecaster2 = Differencer() * global_forecaster1\n",
         "global_forecaster2.fit(y_train, X_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 22,
       "metadata": {},
+      "outputs": [],
       "source": [
         "y_pred_global2 = global_forecaster2.predict(fh=fh, X=X_test)\n",
         "metric_global2 = metric(y_true=y_test, y_pred=y_pred_global2, y_train=y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -423,16 +2028,16 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 23,
       "metadata": {},
+      "outputs": [],
       "source": [
         "local_forecaster2 = ForecastByLevel(global_forecaster2, groupby=\"local\")\n",
         "local_forecaster2.fit(y_train, X=X_train)\n",
         "\n",
         "y_pred_local2 = local_forecaster2.predict(fh=fh, X=X_test)\n",
         "metric_local2 = metric(y_true=y_test, y_pred=y_pred_local2, y_train=y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -443,15 +2048,64 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 24,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Global (1)</th>\n",
+              "      <th>Local (1)</th>\n",
+              "      <th>Global (2)</th>\n",
+              "      <th>Local (2)</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>MSE</th>\n",
+              "      <td>41.057873</td>\n",
+              "      <td>23.720592</td>\n",
+              "      <td>22.238809</td>\n",
+              "      <td>67.626298</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "     Global (1)  Local (1)  Global (2)  Local (2)\n",
+              "MSE   41.057873  23.720592   22.238809  67.626298"
+            ]
+          },
+          "execution_count": 24,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "errors[\"Global (2)\"] = metric_global2\n",
         "errors[\"Local (2)\"] = metric_local2\n",
         "\n",
         "errors"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -467,20 +2121,407 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 25,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-6a2e28bc-f833-4ebc-9b79-4108f65832f0' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    normalization_strategy=&#x27;divide_mean&#x27;, window_length=30)</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('276e1042-ed86-4d2a-bff3-efc99f14ff73') type=\"checkbox\" ><label for=UUID('276e1042-ed86-4d2a-bff3-efc99f14ff73') class='sk-toggleable__label sk-toggleable__label-arrow'>ReductionForecaster</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    normalization_strategy=&#x27;divide_mean&#x27;, window_length=30)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('7037ba2b-59c3-4927-b329-26332e0c0db9') type=\"checkbox\" ><label for=UUID('7037ba2b-59c3-4927-b329-26332e0c0db9') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('c3249f7e-9978-4af0-92af-3f2e00969bf4') type=\"checkbox\" ><label for=UUID('c3249f7e-9978-4af0-92af-3f2e00969bf4') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    normalization_strategy='divide_mean', window_length=30)"
+            ]
+          },
+          "execution_count": 25,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "global_forecaster3 = global_forecaster1.clone().set_params(\n",
         "    normalization_strategy=\"divide_mean\"\n",
         ")\n",
         "\n",
         "global_forecaster3.fit(y_train, X_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 26,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Global (1)</th>\n",
+              "      <th>Local (1)</th>\n",
+              "      <th>Global (2)</th>\n",
+              "      <th>Local (2)</th>\n",
+              "      <th>Global 3 (window norm)</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>MSE</th>\n",
+              "      <td>41.057873</td>\n",
+              "      <td>23.720592</td>\n",
+              "      <td>22.238809</td>\n",
+              "      <td>67.626298</td>\n",
+              "      <td>15.317953</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "     Global (1)  Local (1)  Global (2)  Local (2)  Global 3 (window norm)\n",
+              "MSE   41.057873  23.720592   22.238809  67.626298               15.317953"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "# Predict\n",
         "y_pred_global3 = global_forecaster3.predict(fh=fh, X=X_test)\n",
@@ -491,9 +2532,7 @@
         "errors[\"Global 3 (window norm)\"] = metric_global3\n",
         "\n",
         "display(errors)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -511,7 +2550,354 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 27,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-e894bdb8-1d7c-43bb-8dfa-08c10eb875e8' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ForecastingPipeline(steps=[FourierFeatures(fourier_terms_list=[1, 1], freq=&#x27;D&#x27;,\n",
+              "                                           sp_list=[365.25, 30.4375]),\n",
+              "                           ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                               normalization_strategy=&#x27;divide_mean&#x27;,\n",
+              "                                               window_length=30)])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('766fdcae-48de-488d-a0e4-2a3d12576acc') type=\"checkbox\" ><label for=UUID('766fdcae-48de-488d-a0e4-2a3d12576acc') class='sk-toggleable__label sk-toggleable__label-arrow'>ForecastingPipeline<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.compose.ForecastingPipeline.html\">?<span>Documentation for ForecastingPipeline</span></a></label><div class=\"sk-toggleable__content\"><pre>ForecastingPipeline(steps=[FourierFeatures(fourier_terms_list=[1, 1], freq=&#x27;D&#x27;,\n",
+              "                                           sp_list=[365.25, 30.4375]),\n",
+              "                           ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                               normalization_strategy=&#x27;divide_mean&#x27;,\n",
+              "                                               window_length=30)])</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('43cf84b0-3274-486b-8b48-e5569ba6361c') type=\"checkbox\" ><label for=UUID('43cf84b0-3274-486b-8b48-e5569ba6361c') class='sk-toggleable__label sk-toggleable__label-arrow'>FourierFeatures<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.fourier.FourierFeatures.html\">?<span>Documentation for FourierFeatures</span></a></label><div class=\"sk-toggleable__content\"><pre>FourierFeatures(fourier_terms_list=[1, 1], freq=&#x27;D&#x27;, sp_list=[365.25, 30.4375])</pre></div></div></div><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('5f9aff33-1993-4c66-b2db-7ea0c9ce9453') type=\"checkbox\" ><label for=UUID('5f9aff33-1993-4c66-b2db-7ea0c9ce9453') class='sk-toggleable__label sk-toggleable__label-arrow'>ReductionForecaster</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    normalization_strategy=&#x27;divide_mean&#x27;, window_length=30)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('d16e9d71-0c83-46f5-a0d5-d30c9b100d59') type=\"checkbox\" ><label for=UUID('d16e9d71-0c83-46f5-a0d5-d30c9b100d59') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('7894d607-e99c-4c75-87b0-e993d91bc1a3') type=\"checkbox\" ><label for=UUID('7894d607-e99c-4c75-87b0-e993d91bc1a3') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div></div></div></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "ForecastingPipeline(steps=[FourierFeatures(fourier_terms_list=[1, 1], freq='D',\n",
+              "                                           sp_list=[365.25, 30.4375]),\n",
+              "                           ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                               normalization_strategy='divide_mean',\n",
+              "                                               window_length=30)])"
+            ]
+          },
+          "execution_count": 27,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.transformations.series.fourier import FourierFeatures\n",
         "\n",
@@ -521,22 +2907,76 @@
         "\n",
         "global_forecaster4 = fourier_features**global_forecaster3\n",
         "global_forecaster4.fit(y_train, X_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 28,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Global (1)</th>\n",
+              "      <th>Local (1)</th>\n",
+              "      <th>Global (2)</th>\n",
+              "      <th>Local (2)</th>\n",
+              "      <th>Global 3 (window norm)</th>\n",
+              "      <th>Global 4 (fourier)</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>MSE</th>\n",
+              "      <td>41.057873</td>\n",
+              "      <td>23.720592</td>\n",
+              "      <td>22.238809</td>\n",
+              "      <td>67.626298</td>\n",
+              "      <td>15.317953</td>\n",
+              "      <td>15.143648</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "     Global (1)  Local (1)  Global (2)  Local (2)  Global 3 (window norm)  \\\n",
+              "MSE   41.057873  23.720592   22.238809  67.626298               15.317953   \n",
+              "\n",
+              "     Global 4 (fourier)  \n",
+              "MSE           15.143648  "
+            ]
+          },
+          "execution_count": 28,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_pred_global4 = global_forecaster4.predict(fh=fh, X=X_test)\n",
         "metric_global4 = metric(y_true=y_test, y_pred=y_pred_global4, y_train=y_train)\n",
         "\n",
         "errors[\"Global 4 (fourier)\"] = metric_global4\n",
         "errors"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -558,7 +2998,20 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 29,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1000x600 with 4 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "# | echo: false\n",
         "import numpy as np\n",
@@ -654,13 +3107,385 @@
         "\n",
         "plt.tight_layout()\n",
         "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 30,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625 a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-acdca03e-53cd-4bf7-bd47-fa4eaa541625' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GroupbyCategoryForecaster(forecasters={&#x27;erratic&#x27;: ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                      normalization_strategy=&#x27;divide_mean&#x27;,\n",
+              "                                                                      window_length=30),\n",
+              "                                       &#x27;intermittent&#x27;: ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                           normalization_strategy=&#x27;divide_mean&#x27;,\n",
+              "                                                                           window_length=30),\n",
+              "                                       &#x27;lumpy&#x27;: ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                    normalization_strategy=&#x27;divide_mean&#x27;,\n",
+              "                                                                    window_length=30),\n",
+              "                                       &#x27;smooth&#x27;: ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                     normalization_strategy=&#x27;divide_mean&#x27;,\n",
+              "                                                                     window_length=30)},\n",
+              "                          transformer=ADICVTransformer(features=[&#x27;class&#x27;]))</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('ea1fdbd8-193f-4845-bf88-e89e4d6a6a35') type=\"checkbox\" ><label for=UUID('ea1fdbd8-193f-4845-bf88-e89e4d6a6a35') class='sk-toggleable__label sk-toggleable__label-arrow'>GroupbyCategoryForecaster<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.compose.GroupbyCategoryForecaster.html\">?<span>Documentation for GroupbyCategoryForecaster</span></a></label><div class=\"sk-toggleable__content\"><pre>GroupbyCategoryForecaster(forecasters={&#x27;erratic&#x27;: ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                      normalization_strategy=&#x27;divide_mean&#x27;,\n",
+              "                                                                      window_length=30),\n",
+              "                                       &#x27;intermittent&#x27;: ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                           normalization_strategy=&#x27;divide_mean&#x27;,\n",
+              "                                                                           window_length=30),\n",
+              "                                       &#x27;lumpy&#x27;: ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                    normalization_strategy=&#x27;divide_mean&#x27;,\n",
+              "                                                                    window_length=30),\n",
+              "                                       &#x27;smooth&#x27;: ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                     normalization_strategy=&#x27;divide_mean&#x27;,\n",
+              "                                                                     window_length=30)},\n",
+              "                          transformer=ADICVTransformer(features=[&#x27;class&#x27;]))</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('4982af4d-de1b-4b10-9e13-022534efc00e') type=\"checkbox\" ><label for=UUID('4982af4d-de1b-4b10-9e13-022534efc00e') class='sk-toggleable__label sk-toggleable__label-arrow'>ADICVTransformer</label><div class=\"sk-toggleable__content\"><pre>ADICVTransformer(features=[&#x27;class&#x27;])</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('dc2ac117-98cc-4307-87a4-94239bece394') type=\"checkbox\" ><label for=UUID('dc2ac117-98cc-4307-87a4-94239bece394') class='sk-toggleable__label sk-toggleable__label-arrow'>ADICVTransformer<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.transformations.series.adi_cv.ADICVTransformer.html\">?<span>Documentation for ADICVTransformer</span></a></label><div class=\"sk-toggleable__content\"><pre>ADICVTransformer(features=[&#x27;class&#x27;])</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('298babbd-10e5-46a3-a45e-61c969547403') type=\"checkbox\" ><label for=UUID('298babbd-10e5-46a3-a45e-61c969547403') class='sk-toggleable__label sk-toggleable__label-arrow'>smooth</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    normalization_strategy=&#x27;divide_mean&#x27;, window_length=30)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('423129b4-d512-4fb3-afd3-bf46ecc46712') type=\"checkbox\" ><label for=UUID('423129b4-d512-4fb3-afd3-bf46ecc46712') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('f39581ef-ca2f-4aea-807c-37dc1456151b') type=\"checkbox\" ><label for=UUID('f39581ef-ca2f-4aea-807c-37dc1456151b') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('329d46f8-05d9-42fb-b413-a05e89c04fc7') type=\"checkbox\" ><label for=UUID('329d46f8-05d9-42fb-b413-a05e89c04fc7') class='sk-toggleable__label sk-toggleable__label-arrow'>erratic</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    normalization_strategy=&#x27;divide_mean&#x27;, window_length=30)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('510be7dd-6bf8-406a-8577-7688af29e8cc') type=\"checkbox\" ><label for=UUID('510be7dd-6bf8-406a-8577-7688af29e8cc') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('76278ec0-932c-456c-8bd0-bdac7875412d') type=\"checkbox\" ><label for=UUID('76278ec0-932c-456c-8bd0-bdac7875412d') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('74fe37a7-6655-4d7f-875f-ca641cf05a5f') type=\"checkbox\" ><label for=UUID('74fe37a7-6655-4d7f-875f-ca641cf05a5f') class='sk-toggleable__label sk-toggleable__label-arrow'>intermittent</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    normalization_strategy=&#x27;divide_mean&#x27;, window_length=30)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('4e199400-0b0f-4eb4-9919-629078a88634') type=\"checkbox\" ><label for=UUID('4e199400-0b0f-4eb4-9919-629078a88634') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('94810e0e-3ee6-4c85-9a62-dc5bfe06b778') type=\"checkbox\" ><label for=UUID('94810e0e-3ee6-4c85-9a62-dc5bfe06b778') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('0a1ca45f-c161-498b-afb7-22743296fcc0') type=\"checkbox\" ><label for=UUID('0a1ca45f-c161-498b-afb7-22743296fcc0') class='sk-toggleable__label sk-toggleable__label-arrow'>lumpy</label><div class=\"sk-toggleable__content\"><pre>ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                    normalization_strategy=&#x27;divide_mean&#x27;, window_length=30)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('d740000e-41e7-4dfe-9639-eb1952679000') type=\"checkbox\" ><label for=UUID('d740000e-41e7-4dfe-9639-eb1952679000') class='sk-toggleable__label sk-toggleable__label-arrow'>estimator: LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('a9123bf9-d35d-458e-a6de-1c161c0868d3') type=\"checkbox\" ><label for=UUID('a9123bf9-d35d-458e-a6de-1c161c0868d3') class='sk-toggleable__label sk-toggleable__label-arrow'>LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(random_state=42, verbose=-1)</pre></div></div></div></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class='sk-label-container'><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('d5171da8-f091-4ce3-b1e9-5a8b16119add') type=\"checkbox\" ><label for=UUID('d5171da8-f091-4ce3-b1e9-5a8b16119add') class='sk-toggleable__label sk-toggleable__label-arrow'>fallback_forecaster</label><div class=\"sk-toggleable__content\"><pre>None</pre></div></div></div><div class=\"sk-serial\"><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('0e4e9277-601a-4977-b2d9-0ab3f8c50339') type=\"checkbox\" ><label for=UUID('0e4e9277-601a-4977-b2d9-0ab3f8c50339') class='sk-toggleable__label sk-toggleable__label-arrow'>None</label><div class=\"sk-toggleable__content\"><pre>None</pre></div></div></div></div></div></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "GroupbyCategoryForecaster(forecasters={'erratic': ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                      normalization_strategy='divide_mean',\n",
+              "                                                                      window_length=30),\n",
+              "                                       'intermittent': ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                           normalization_strategy='divide_mean',\n",
+              "                                                                           window_length=30),\n",
+              "                                       'lumpy': ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                    normalization_strategy='divide_mean',\n",
+              "                                                                    window_length=30),\n",
+              "                                       'smooth': ReductionForecaster(estimator=LGBMRegressor(random_state=42, verbose=-1),\n",
+              "                                                                     normalization_strategy='divide_mean',\n",
+              "                                                                     window_length=30)},\n",
+              "                          transformer=ADICVTransformer(features=['class']))"
+            ]
+          },
+          "execution_count": 30,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.forecasting.compose import GroupbyCategoryForecaster\n",
         "from sktime.transformations.series.adi_cv import ADICVTransformer\n",
@@ -677,21 +3502,30 @@
         "\n",
         "\n",
         "group_forecaster.fit(y_train, X_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 31,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "np.float64(53.56051503265084)"
+            ]
+          },
+          "execution_count": 31,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_pred_group = group_forecaster.predict(fh=fh, X=X_test)\n",
         "metric_group = metric(y_true=y_test, y_pred=y_pred_group, y_train=y_train)\n",
         "\n",
         "metric_group"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -712,12 +3546,23 @@
   ],
   "metadata": {
     "kernelspec": {
-      "name": "python3",
+      "display_name": "tsbook-py3.11",
       "language": "python",
-      "display_name": "Python 3 (ipykernel)",
-      "path": "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/share/jupyter/kernels/python3"
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.11"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 4
-}
\ No newline at end of file
+}
diff --git a/notebooks/part2/04_hierarchical_forecasting.ipynb b/notebooks/part2/04_hierarchical_forecasting.ipynb
index 95e9393..19cf830 100644
--- a/notebooks/part2/04_hierarchical_forecasting.ipynb
+++ b/notebooks/part2/04_hierarchical_forecasting.ipynb
@@ -54,7 +54,9 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 1,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# | echo: false\n",
         "\n",
@@ -63,21 +65,19 @@
         "import matplotlib.pyplot as plt\n",
         "\n",
         "warnings.filterwarnings(\"ignore\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 2,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from tsbook.datasets.retail import SyntheticRetail\n",
         "\n",
         "dataset = SyntheticRetail(\"hierarchical\")\n",
         "y_train, X_train, y_test, X_test = dataset.load(\"y_train\", \"X_train\", \"y_test\", \"X_test\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -90,12 +90,123 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 3,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>sales</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>group_id</th>\n",
+              "      <th>sku_id</th>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">-1</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">20</th>\n",
+              "      <th>2020-01-01</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-02</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-03</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-04</th>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-05</th>\n",
+              "      <td>2</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">__total</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">__total</th>\n",
+              "      <th>2024-07-01</th>\n",
+              "      <td>2000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-02</th>\n",
+              "      <td>1616</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-03</th>\n",
+              "      <td>1917</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-04</th>\n",
+              "      <td>2384</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-05</th>\n",
+              "      <td>2462</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>51088 rows × 1 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                             sales\n",
+              "group_id sku_id  date             \n",
+              "-1       20      2020-01-01      0\n",
+              "                 2020-01-02      0\n",
+              "                 2020-01-03      0\n",
+              "                 2020-01-04      0\n",
+              "                 2020-01-05      2\n",
+              "...                            ...\n",
+              "__total  __total 2024-07-01   2000\n",
+              "                 2024-07-02   1616\n",
+              "                 2024-07-03   1917\n",
+              "                 2024-07-04   2384\n",
+              "                 2024-07-05   2462\n",
+              "\n",
+              "[51088 rows x 1 columns]"
+            ]
+          },
+          "execution_count": 3,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_train"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -106,12 +217,23 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 4,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "31"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_train.index.droplevel(-1).nunique()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -122,12 +244,80 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 5,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>sales</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2020-01-01</th>\n",
+              "      <td>4</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-02</th>\n",
+              "      <td>2</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-03</th>\n",
+              "      <td>3</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-04</th>\n",
+              "      <td>14</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-05</th>\n",
+              "      <td>16</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            sales\n",
+              "date             \n",
+              "2020-01-01      4\n",
+              "2020-01-02      2\n",
+              "2020-01-03      3\n",
+              "2020-01-04     14\n",
+              "2020-01-05     16"
+            ]
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_train.loc[(-1, \"__total\")].head()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -138,12 +328,113 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 6,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>sales</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2020-01-01</th>\n",
+              "      <td>24</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-02</th>\n",
+              "      <td>19</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-03</th>\n",
+              "      <td>14</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-04</th>\n",
+              "      <td>23</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2020-01-05</th>\n",
+              "      <td>23</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-01</th>\n",
+              "      <td>2000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-02</th>\n",
+              "      <td>1616</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-03</th>\n",
+              "      <td>1917</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-04</th>\n",
+              "      <td>2384</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-05</th>\n",
+              "      <td>2462</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>1648 rows × 1 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            sales\n",
+              "date             \n",
+              "2020-01-01     24\n",
+              "2020-01-02     19\n",
+              "2020-01-03     14\n",
+              "2020-01-04     23\n",
+              "2020-01-05     23\n",
+              "...           ...\n",
+              "2024-07-01   2000\n",
+              "2024-07-02   1616\n",
+              "2024-07-03   1917\n",
+              "2024-07-04   2384\n",
+              "2024-07-05   2462\n",
+              "\n",
+              "[1648 rows x 1 columns]"
+            ]
+          },
+          "execution_count": 6,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_train.loc[(\"__total\", \"__total\")]"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -154,12 +445,23 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 7,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "31"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "y_train.index.droplevel(-1).nunique()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -172,16 +474,18 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 8,
       "metadata": {},
+      "outputs": [],
       "source": [
         "fh = y_test.index.get_level_values(-1).unique()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 9,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from tsbook.forecasting.reduction import ReductionForecaster\n",
         "from lightgbm import LGBMRegressor\n",
@@ -193,9 +497,7 @@
         ")\n",
         "forecaster.fit(y_train, X=X_train)\n",
         "y_pred = forecaster.predict(fh, X=X_test)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -207,14 +509,125 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 10,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>sales</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>group_id</th>\n",
+              "      <th>sku_id</th>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">-1</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">20</th>\n",
+              "      <th>2024-07-06</th>\n",
+              "      <td>0.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-07</th>\n",
+              "      <td>0.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-08</th>\n",
+              "      <td>0.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-09</th>\n",
+              "      <td>0.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-10</th>\n",
+              "      <td>0.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">__total</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">__total</th>\n",
+              "      <th>2024-12-28</th>\n",
+              "      <td>55.335283</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-29</th>\n",
+              "      <td>156.831394</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-30</th>\n",
+              "      <td>210.198180</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-31</th>\n",
+              "      <td>190.297510</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2025-01-01</th>\n",
+              "      <td>13.594787</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5580 rows × 1 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                  sales\n",
+              "group_id sku_id  date                  \n",
+              "-1       20      2024-07-06    0.000000\n",
+              "                 2024-07-07    0.000000\n",
+              "                 2024-07-08    0.000000\n",
+              "                 2024-07-09    0.000000\n",
+              "                 2024-07-10    0.000000\n",
+              "...                                 ...\n",
+              "__total  __total 2024-12-28   55.335283\n",
+              "                 2024-12-29  156.831394\n",
+              "                 2024-12-30  210.198180\n",
+              "                 2024-12-31  190.297510\n",
+              "                 2025-01-01   13.594787\n",
+              "\n",
+              "[5580 rows x 1 columns]"
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.transformations.hierarchical.aggregate import Aggregator\n",
         "\n",
         "Aggregator().fit_transform(y_pred) - y_pred"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -253,7 +666,9 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 11,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from sktime.transformations.hierarchical.reconcile import BottomUpReconciler\n",
         "\n",
@@ -261,9 +676,7 @@
         "bottom_up.fit(y_train)\n",
         "\n",
         "y_pred_bottomup = bottom_up.predict(fh=fh)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -274,12 +687,123 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 12,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>sales</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>group_id</th>\n",
+              "      <th>sku_id</th>\n",
+              "      <th>date</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">-1</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">20</th>\n",
+              "      <th>2024-07-06</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-07</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-08</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-09</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-07-10</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"5\" valign=\"top\">__total</th>\n",
+              "      <th rowspan=\"5\" valign=\"top\">__total</th>\n",
+              "      <th>2024-12-28</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-29</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-30</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2024-12-31</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2025-01-01</th>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5580 rows × 1 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                             sales\n",
+              "group_id sku_id  date             \n",
+              "-1       20      2024-07-06    0.0\n",
+              "                 2024-07-07    0.0\n",
+              "                 2024-07-08    0.0\n",
+              "                 2024-07-09    0.0\n",
+              "                 2024-07-10    0.0\n",
+              "...                            ...\n",
+              "__total  __total 2024-12-28    0.0\n",
+              "                 2024-12-29    0.0\n",
+              "                 2024-12-30    0.0\n",
+              "                 2024-12-31    0.0\n",
+              "                 2025-01-01    0.0\n",
+              "\n",
+              "[5580 rows x 1 columns]"
+            ]
+          },
+          "execution_count": 12,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "Aggregator().fit_transform(y_pred_bottomup) - y_pred_bottomup"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -323,7 +847,9 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 13,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from sktime.transformations.hierarchical.reconcile import TopdownReconciler\n",
         "\n",
@@ -331,9 +857,7 @@
         "top_down_fcst.fit(y_train)\n",
         "\n",
         "y_pred_topdown = top_down_fcst.predict(fh=fh)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -367,20 +891,33 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 14,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from sktime.transformations.hierarchical.reconcile import OptimalReconciler\n",
         "\n",
         "optimal = OptimalReconciler(\"ols\") * forecaster\n",
         "optimal.fit(y_train)\n",
         "y_pred_optimal = optimal.predict(fh=fh)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 15,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1600x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "# | code-fold: true\n",
         "from sktime.utils.plotting import plot_series\n",
@@ -399,9 +936,7 @@
         ")\n",
         "plt.xlim(pd.to_datetime(\"2024-05-01\"), None)\n",
         "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -412,7 +947,9 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 16,
       "metadata": {},
+      "outputs": [],
       "source": [
         "from sktime.forecasting.reconcile import ReconcilerForecaster\n",
         "\n",
@@ -423,9 +960,7 @@
         "\n",
         "mint_forecaster.fit(y_train)\n",
         "y_pred_mint = mint_forecaster.predict(fh=fh)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -436,7 +971,63 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 17,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Baseline</th>\n",
+              "      <th>BottomUpReconciler</th>\n",
+              "      <th>TopDownReconciler</th>\n",
+              "      <th>OptimalReconciler (ols)</th>\n",
+              "      <th>Mint Reconciler</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>Mean Absolute Squared Error</th>\n",
+              "      <td>40.179149</td>\n",
+              "      <td>26.079303</td>\n",
+              "      <td>90.661393</td>\n",
+              "      <td>59.86903</td>\n",
+              "      <td>22.794349</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                              Baseline  BottomUpReconciler  TopDownReconciler  \\\n",
+              "Mean Absolute Squared Error  40.179149           26.079303          90.661393   \n",
+              "\n",
+              "                             OptimalReconciler (ols)  Mint Reconciler  \n",
+              "Mean Absolute Squared Error                 59.86903        22.794349  "
+            ]
+          },
+          "execution_count": 17,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.performance_metrics.forecasting import MeanSquaredScaledError\n",
         "\n",
@@ -452,19 +1043,28 @@
         "    },\n",
         "    index=[\"Mean Absolute Squared Error\"],\n",
         ")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     }
   ],
   "metadata": {
     "kernelspec": {
-      "name": "python3",
+      "display_name": "tsbook-py3.11",
       "language": "python",
-      "display_name": "Python 3 (ipykernel)",
-      "path": "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/share/jupyter/kernels/python3"
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.11"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 4
-}
\ No newline at end of file
+}
diff --git a/notebooks/part2/05_deep_learning.ipynb b/notebooks/part2/05_deep_learning.ipynb
index b0fb454..f0e4ba4 100644
--- a/notebooks/part2/05_deep_learning.ipynb
+++ b/notebooks/part2/05_deep_learning.ipynb
@@ -18,32 +18,34 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 1,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# | echo: false\n",
         "import warnings\n",
         "\n",
         "warnings.filterwarnings(\"ignore\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 2,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# | code-fold: true\n",
         "import pandas as pd\n",
         "import matplotlib.pyplot as plt\n",
         "\n",
         "from sktime.utils.plotting import plot_series"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 3,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# | code-fold: true\n",
         "\n",
@@ -55,9 +57,7 @@
         ")\n",
         "\n",
         "fh = y_test.index.get_level_values(-1).unique()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -97,7 +97,455 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 4,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "💡 Tip: For seamless cloud uploads and versioning, try installing [litmodels](https://pypi.org/project/litmodels/) to enable LitModelCheckpoint, which syncs automatically with the Lightning model registry.\n",
+            "GPU available: True (mps), used: True\n",
+            "TPU available: False, using: 0 TPU cores\n",
+            "HPU available: False, using: 0 HPUs\n",
+            "\n",
+            "  | Name            | Type       | Params | Mode \n",
+            "-------------------------------------------------------\n",
+            "0 | loss            | MASE       | 0      | train\n",
+            "1 | logging_metrics | ModuleList | 0      | train\n",
+            "2 | net_blocks      | ModuleList | 1.4 M  | train\n",
+            "-------------------------------------------------------\n",
+            "1.4 M     Trainable params\n",
+            "0         Non-trainable params\n",
+            "1.4 M     Total params\n",
+            "5.484     Total estimated model params size (MB)\n",
+            "60        Modules in train mode\n",
+            "0         Modules in eval mode\n"
+          ]
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "58a65c86bb054b9fafb62cec6371c227",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Sanity Checking: |          | 0/? [00:00<?, ?it/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "d090e7d56248444f9efffc9adc830e89",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Training: |          | 0/? [00:00<?, ?it/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "f1613e839e8745a9be2f76f096aef000",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Validation: |          | 0/? [00:00<?, ?it/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "`Trainer.fit` stopped: `max_epochs=1` reached.\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<style>#sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c {\n",
+              "    /* Definition of color scheme common for light and dark mode */\n",
+              "    --sklearn-color-text: black;\n",
+              "    --sklearn-color-line: gray;\n",
+              "    /* Definition of color scheme for objects */\n",
+              "    --sklearn-color-level-0: #fff5e6;\n",
+              "    --sklearn-color-level-1: #f6e4d2;\n",
+              "    --sklearn-color-level-2: #ffe0b3;\n",
+              "    --sklearn-color-level-3: chocolate;\n",
+              "\n",
+              "    /* Specific color for light theme */\n",
+              "    --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, white));\n",
+              "    --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, black));\n",
+              "    --sklearn-color-icon: #696969;\n",
+              "\n",
+              "    @media (prefers-color-scheme: dark) {\n",
+              "      /* Redefinition of color scheme for dark theme */\n",
+              "      --sklearn-color-text-on-default-background: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-background: var(--theme-background, var(--jp-layout-color0, #111));\n",
+              "      --sklearn-color-border-box: var(--theme-code-foreground, var(--jp-content-font-color1, white));\n",
+              "      --sklearn-color-icon: #878787;\n",
+              "    }\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c pre {\n",
+              "    padding: 0;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c input.sk-hidden--visually {\n",
+              "    border: 0;\n",
+              "    clip: rect(1px 1px 1px 1px);\n",
+              "    clip: rect(1px, 1px, 1px, 1px);\n",
+              "    height: 1px;\n",
+              "    margin: -1px;\n",
+              "    overflow: hidden;\n",
+              "    padding: 0;\n",
+              "    position: absolute;\n",
+              "    width: 1px;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-dashed-wrapped {\n",
+              "    border: 1px dashed var(--sklearn-color-line);\n",
+              "    margin: 0 0.4em 0.5em 0.4em;\n",
+              "    box-sizing: border-box;\n",
+              "    padding-bottom: 0.4em;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-container {\n",
+              "    /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+              "       but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+              "       so we also need the `!important` here to be able to override the\n",
+              "       default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+              "       See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+              "    display: inline-block !important;\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-text-repr-fallback {\n",
+              "    display: none;\n",
+              "  }\n",
+              "\n",
+              "  div.sk-parallel-item,\n",
+              "  div.sk-serial,\n",
+              "  div.sk-item {\n",
+              "    /* draw centered vertical line to link estimators */\n",
+              "    background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+              "    background-size: 2px 100%;\n",
+              "    background-repeat: no-repeat;\n",
+              "    background-position: center center;\n",
+              "  }\n",
+              "\n",
+              "  /* Parallel-specific style estimator block */\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-parallel-item::after {\n",
+              "    content: \"\";\n",
+              "    width: 100%;\n",
+              "    border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+              "    flex-grow: 1;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-parallel {\n",
+              "    display: flex;\n",
+              "    align-items: stretch;\n",
+              "    justify-content: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    position: relative;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-parallel-item {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-parallel-item:first-child::after {\n",
+              "    align-self: flex-end;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-parallel-item:last-child::after {\n",
+              "    align-self: flex-start;\n",
+              "    width: 50%;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-parallel-item:only-child::after {\n",
+              "    width: 0;\n",
+              "  }\n",
+              "\n",
+              "  /* Serial-specific style estimator block */\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-serial {\n",
+              "    display: flex;\n",
+              "    flex-direction: column;\n",
+              "    align-items: center;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    padding-right: 1em;\n",
+              "    padding-left: 1em;\n",
+              "  }\n",
+              "\n",
+              "\n",
+              "  /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+              "  clickable and can be expanded/collapsed.\n",
+              "  - Pipeline and ColumnTransformer use this feature and define the default style\n",
+              "  - Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+              "  */\n",
+              "\n",
+              "  /* Pipeline and ColumnTransformer style (default) */\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-toggleable {\n",
+              "    /* Default theme specific background. It is overwritten whether we have a\n",
+              "    specific estimator or a Pipeline/ColumnTransformer */\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable label */\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c label.sk-toggleable__label {\n",
+              "    cursor: pointer;\n",
+              "    display: block;\n",
+              "    width: 100%;\n",
+              "    margin-bottom: 0;\n",
+              "    padding: 0.5em;\n",
+              "    box-sizing: border-box;\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c label.sk-toggleable__label-arrow:before {\n",
+              "    /* Arrow on the left of the label */\n",
+              "    content: \"▸\";\n",
+              "    float: left;\n",
+              "    margin-right: 0.25em;\n",
+              "    color: var(--sklearn-color-icon);\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c label.sk-toggleable__label-arrow:hover:before {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "  }\n",
+              "\n",
+              "  /* Toggleable content - dropdown */\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-toggleable__content {\n",
+              "    max-height: 0;\n",
+              "    max-width: 0;\n",
+              "    overflow: hidden;\n",
+              "    text-align: left;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-toggleable__content pre {\n",
+              "    margin: 0.2em;\n",
+              "    border-radius: 0.25em;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+              "    /* Expand drop-down */\n",
+              "    max-height: 200px;\n",
+              "    max-width: 100%;\n",
+              "    overflow: auto;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+              "    content: \"▾\";\n",
+              "  }\n",
+              "\n",
+              "  /* Pipeline/ColumnTransformer-specific style */\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific style */\n",
+              "\n",
+              "  /* Colorize estimator box */\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+              "    /* unfitted */\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-label label.sk-toggleable__label,\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-label label {\n",
+              "    /* The background is the default theme color */\n",
+              "    color: var(--sklearn-color-text-on-default-background);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover, darken the color of the background */\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-label:hover label.sk-toggleable__label {\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator label */\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-label label {\n",
+              "    font-family: monospace;\n",
+              "    font-weight: bold;\n",
+              "    display: inline-block;\n",
+              "    line-height: 1.2em;\n",
+              "  }\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-label-container {\n",
+              "    text-align: center;\n",
+              "  }\n",
+              "\n",
+              "  /* Estimator-specific */\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-estimator {\n",
+              "    font-family: monospace;\n",
+              "    border: 1px dotted var(--sklearn-color-border-box);\n",
+              "    border-radius: 0.25em;\n",
+              "    box-sizing: border-box;\n",
+              "    margin-bottom: 0.5em;\n",
+              "    background-color: var(--sklearn-color-level-0);\n",
+              "  }\n",
+              "\n",
+              "  /* on hover */\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c div.sk-estimator:hover {\n",
+              "    background-color: var(--sklearn-color-level-2);\n",
+              "  }\n",
+              "\n",
+              "  /* Specification for estimator info */\n",
+              "\n",
+              "  .sk-estimator-doc-link,\n",
+              "  a:link.sk-estimator-doc-link,\n",
+              "  a:visited.sk-estimator-doc-link {\n",
+              "    float: right;\n",
+              "    font-size: smaller;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1em;\n",
+              "    height: 1em;\n",
+              "    width: 1em;\n",
+              "    text-decoration: none !important;\n",
+              "    margin-left: 1ex;\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover,\n",
+              "  div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+              "  .sk-estimator-doc-link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "\n",
+              "  /* Span, style for the box shown on hovering the info icon */\n",
+              "  .sk-estimator-doc-link span {\n",
+              "    display: none;\n",
+              "    z-index: 9999;\n",
+              "    position: relative;\n",
+              "    font-weight: normal;\n",
+              "    right: .2ex;\n",
+              "    padding: .5ex;\n",
+              "    margin: .5ex;\n",
+              "    width: min-content;\n",
+              "    min-width: 20ex;\n",
+              "    max-width: 50ex;\n",
+              "    color: var(--sklearn-color-text);\n",
+              "    box-shadow: 2pt 2pt 4pt #999;\n",
+              "    background: var(--sklearn-color-level-0);\n",
+              "    border: .5pt solid var(--sklearn-color-level-3);\n",
+              "  }\n",
+              "\n",
+              "  .sk-estimator-doc-link:hover span {\n",
+              "    display: block;\n",
+              "  }\n",
+              "\n",
+              "  /* \"?\"-specific style due to the `<a>` HTML tag */\n",
+              "\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c a.estimator_doc_link {\n",
+              "    float: right;\n",
+              "    font-size: 1rem;\n",
+              "    line-height: 1em;\n",
+              "    font-family: monospace;\n",
+              "    background-color: var(--sklearn-color-background);\n",
+              "    border-radius: 1rem;\n",
+              "    height: 1rem;\n",
+              "    width: 1rem;\n",
+              "    text-decoration: none;\n",
+              "    color: var(--sklearn-color-level-1);\n",
+              "    border: var(--sklearn-color-level-1) 1pt solid;\n",
+              "  }\n",
+              "\n",
+              "  /* On hover */\n",
+              "  #sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c a.estimator_doc_link:hover {\n",
+              "    background-color: var(--sklearn-color-level-3);\n",
+              "    color: var(--sklearn-color-background);\n",
+              "    text-decoration: none;\n",
+              "  }\n",
+              "</style><div id='sk-7a8f0bdc-06d5-478c-b0b5-b63d9e4df67c' class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>PytorchForecastingNBeats(dataset_params={&#x27;max_encoder_length&#x27;: 120,\n",
+              "                                         &#x27;target_normalizer&#x27;: EncoderNormalizer(\n",
+              "\tmethod=&#x27;standard&#x27;,\n",
+              "\tcenter=True,\n",
+              "\tmax_length=None,\n",
+              "\ttransformation=None,\n",
+              "\tmethod_kwargs={}\n",
+              ")},\n",
+              "                         model_params={&#x27;context_length&#x27;: 120,\n",
+              "                                       &#x27;expansion_coefficient_lengths&#x27;: [2, 5],\n",
+              "                                       &#x27;learning_rate&#x27;: 0.001,\n",
+              "                                       &#x27;num_blocks&#x27;: [2, 2],\n",
+              "                                       &#x27;stack_types&#x27;: [&#x27;trend&#x27;, &#x27;seasonality&#x27;]},\n",
+              "                         train_to_dataloader_params={&#x27;batch_size&#x27;: 256},\n",
+              "                         trainer_params={&#x27;max_epochs&#x27;: 1})</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class=\"sk-container\" hidden><div class='sk-item'><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=UUID('6db3b599-ca17-4fae-96dc-b932c3eb896c') type=\"checkbox\" checked><label for=UUID('6db3b599-ca17-4fae-96dc-b932c3eb896c') class='sk-toggleable__label sk-toggleable__label-arrow'>PytorchForecastingNBeats<a class=\"sk-estimator-doc-link\" rel=\"noreferrer\" target=\"_blank\" href=\"https://www.sktime.net/en/v0.39.0/api_reference/auto_generated/sktime.forecasting.pytorchforecasting.PytorchForecastingNBeats.html\">?<span>Documentation for PytorchForecastingNBeats</span></a></label><div class=\"sk-toggleable__content\"><pre>PytorchForecastingNBeats(dataset_params={&#x27;max_encoder_length&#x27;: 120,\n",
+              "                                         &#x27;target_normalizer&#x27;: EncoderNormalizer(\n",
+              "\tmethod=&#x27;standard&#x27;,\n",
+              "\tcenter=True,\n",
+              "\tmax_length=None,\n",
+              "\ttransformation=None,\n",
+              "\tmethod_kwargs={}\n",
+              ")},\n",
+              "                         model_params={&#x27;context_length&#x27;: 120,\n",
+              "                                       &#x27;expansion_coefficient_lengths&#x27;: [2, 5],\n",
+              "                                       &#x27;learning_rate&#x27;: 0.001,\n",
+              "                                       &#x27;num_blocks&#x27;: [2, 2],\n",
+              "                                       &#x27;stack_types&#x27;: [&#x27;trend&#x27;, &#x27;seasonality&#x27;]},\n",
+              "                         train_to_dataloader_params={&#x27;batch_size&#x27;: 256},\n",
+              "                         trainer_params={&#x27;max_epochs&#x27;: 1})</pre></div></div></div></div></div>"
+            ],
+            "text/plain": [
+              "PytorchForecastingNBeats(dataset_params={'max_encoder_length': 120,\n",
+              "                                         'target_normalizer': EncoderNormalizer(\n",
+              "\tmethod='standard',\n",
+              "\tcenter=True,\n",
+              "\tmax_length=None,\n",
+              "\ttransformation=None,\n",
+              "\tmethod_kwargs={}\n",
+              ")},\n",
+              "                         model_params={'context_length': 120,\n",
+              "                                       'expansion_coefficient_lengths': [2, 5],\n",
+              "                                       'learning_rate': 0.001,\n",
+              "                                       'num_blocks': [2, 2],\n",
+              "                                       'stack_types': ['trend', 'seasonality']},\n",
+              "                         train_to_dataloader_params={'batch_size': 256},\n",
+              "                         trainer_params={'max_epochs': 1})"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.forecasting.pytorchforecasting import PytorchForecastingNBeats\n",
         "from pytorch_forecasting.data.encoders import EncoderNormalizer\n",
@@ -121,30 +569,52 @@
         ")\n",
         "\n",
         "nbeats.fit(y_train.astype(float), fh=fh)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 5,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/lib/python3.11/site-packages/sktime/forecasting/base/adapters/_pytorchforecasting.py:655: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
+            "  _y.fillna(0, inplace=True)\n",
+            "💡 Tip: For seamless cloud uploads and versioning, try installing [litmodels](https://pypi.org/project/litmodels/) to enable LitModelCheckpoint, which syncs automatically with the Lightning model registry.\n",
+            "GPU available: True (mps), used: True\n",
+            "TPU available: False, using: 0 TPU cores\n",
+            "HPU available: False, using: 0 HPUs\n"
+          ]
+        }
+      ],
       "source": [
         "y_pred_nbeats = nbeats.predict(fh=fh, X=X_test)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 6,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "np.float64(16.261236396292887)"
+            ]
+          },
+          "execution_count": 6,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from sktime.performance_metrics.forecasting import MeanSquaredScaledError\n",
         "\n",
         "metric = MeanSquaredScaledError(multilevel=\"uniform_average_time\")\n",
         "metric(y_true=y_test, y_pred=y_pred_nbeats, y_train=y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -156,16 +626,27 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 7,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 1000x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "fig, ax = plt.subplots(figsize=(10, 4))\n",
         "y_train.loc[10].plot(ax=ax, label=\"Train\")\n",
         "y_test.loc[10].plot(ax=ax, label=\"Test\")\n",
         "y_pred_nbeats.loc[10].plot(ax=ax, label=\"N-BEATS\")\n",
         "fig.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -181,7 +662,20 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 8,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1000x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "new_y_train = (y_train.loc[0]**2 + y_train.loc[20]).astype(float)\n",
         "new_y_test = (y_test.loc[0]**2 + y_test.loc[20]).astype(float)\n",
@@ -191,9 +685,7 @@
         "new_y_train[\"sales\"].plot.line(ax=ax, label=\"New Train\")\n",
         "new_y_test[\"sales\"].plot.line(ax=ax, label=\"New Test\")\n",
         "fig.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -204,16 +696,42 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 9,
       "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/lib/python3.11/site-packages/sktime/forecasting/base/adapters/_pytorchforecasting.py:655: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
+            "  _y.fillna(0, inplace=True)\n",
+            "💡 Tip: For seamless cloud uploads and versioning, try installing [litmodels](https://pypi.org/project/litmodels/) to enable LitModelCheckpoint, which syncs automatically with the Lightning model registry.\n",
+            "GPU available: True (mps), used: True\n",
+            "TPU available: False, using: 0 TPU cores\n",
+            "HPU available: False, using: 0 HPUs\n"
+          ]
+        }
+      ],
       "source": [
         "y_pred_zeroshot = nbeats.predict(fh=fh, y=new_y_train)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": 10,
       "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1000x400 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
       "source": [
         "fig, ax = plt.subplots(figsize=(10, 4))\n",
         "new_y_train[\"sales\"].plot.line(ax=ax, label=\"New Train\")\n",
@@ -221,19 +739,28 @@
         "y_pred_zeroshot[\"sales\"].plot.line(ax=ax, label=\"N-BEATS Zero-shot\")\n",
         "plt.legend()\n",
         "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     }
   ],
   "metadata": {
     "kernelspec": {
-      "name": "python3",
+      "display_name": "tsbook-py3.11",
       "language": "python",
-      "display_name": "Python 3 (ipykernel)",
-      "path": "/Users/felipeangelim/Workspace/python_brasil_2025/.venv/share/jupyter/kernels/python3"
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.11"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 4
-}
\ No newline at end of file
+}