Update 16_spot_hpt_sklearn_multiclass_classification.ipynb

Author: bartzbeielstein

notebooks/16_spot_hpt_sklearn_multiclass_classification.ipynb

@@ -5,7 +5,7 @@
    "metadata": {},
    "source": [
     "---\n",
-    "title: \"River Hyperparameter Tuning with SPOT Sklearn: Classification\"\n",
+    "title: \"Scikit-learn Hyperparameter Tuning With spotPython - A Tutorial for Classification\"\n",
     "format: html\n",
     "---"
    ]
@@ -561,12 +561,12 @@
     "# core_model  = RidgeCV\n",
     "# core_model = GradientBoostingRegressor\n",
     "# core_model = ElasticNet\n",
-    "# core_model = RandomForestClassifier\n",
+    "core_model = RandomForestClassifier\n",
     "# core_model = SVC\n",
     "# core_model = LogisticRegression\n",
     "# core_model = KNeighborsClassifier\n",
     "# core_model = GradientBoostingClassifier\n",
-    "core_model = HistGradientBoostingClassifier\n",
+    "# core_model = HistGradientBoostingClassifier\n",
     "fun_control = add_core_model_to_fun_control(core_model=core_model,\n",
     "                              fun_control=fun_control,\n",
     "                              hyper_dict=SklearnHyperDict,\n",
@@ -674,6 +674,31 @@
     ":::"
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Multi-class Classification Metrics\n",
+    "\n",
+    "\n",
+    "\"predict_proba\": predict_proba,\n",
+    "\n",
+    "#### MAPK\n",
+    "\n",
+    "metric_sklearn = mapk_score\n",
+    "metric_params: {\"k\": 3},  # default\n",
+    "\n",
+    "#### top_k_accuracy_score\n",
+    "\n",
+    "* top_k_accuracy_score\n",
+    "\n",
+    "#### ROC\n",
+    "\n",
+    "* metric_sklearn = roc_auc_score\n",
+    "* metric_params = {\"multi_class\": \"ovr\"} \n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 18,
@@ -699,15 +724,10 @@
     "# metric_sklearn = average_precision_score\n",
     "\n",
     "fun_control.update({\n",
-    "               \"horizon\": None,\n",
-    "               \"oml_grace_period\": None,\n",
-    "               \"weights\": weights,\n",
-    "               \"step\": None,\n",
     "               \"log_level\": 50,\n",
-    "               \"weight_coeff\": None,\n",
-    "               \"metric_river\": None,\n",
-    "               \"metric_sklearn\": metric_sklearn,\n",
-    "               \"predict_proba\": predict_proba,               \n",
+    "               \"weights\": -1,\n",
+    "               \"metric_sklearn\": mapk_score,\n",
+    "               \"predict_proba\": True,               \n",
     "               \"metric_params\": {\"k\": 3},\n",
     "               })"
    ]