WIP(notebooks): Add SVM with StandardScaler and PCA to sensor model definitions

code/notebooks/stft.ipynb

@@ -690,6 +690,10 @@
    "source": [
     "from src.ml.model_selection import train_and_evaluate_model\n",
     "from sklearn.svm import SVC\n",
+    "from sklearn.pipeline import make_pipeline\n",
+    "from sklearn.preprocessing import StandardScaler\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.decomposition import PCA\n",
     "# Define models for sensor1\n",
     "models_sensor1 = {\n",
     "    # \"Random Forest\": RandomForestClassifier(),\n",
@@ -698,6 +702,12 @@
     "    # \"KNN\": KNeighborsClassifier(),\n",
     "    # \"LDA\": LinearDiscriminantAnalysis(),\n",
     "    \"SVM\": SVC(),\n",
+    "    \"SVM with StandardScaler and PCA\": make_pipeline(\n",
+    "    StandardScaler(),\n",
+    "    PCA(n_components=10),\n",
+    "    SVC(kernel='rbf')\n",
+    "    ),\n",
+    "\n",
     "    # \"XGBoost\": XGBClassifier()\n",
     "}\n",
     "\n",
@@ -721,6 +731,11 @@
     "    # \"KNN\": KNeighborsClassifier(),\n",
     "    # \"LDA\": LinearDiscriminantAnalysis(),\n",
     "    \"SVM\": SVC(),\n",
+    "    \"SVM with StandardScaler and PCA\": make_pipeline(\n",
+    "    StandardScaler(),\n",
+    "    PCA(n_components=10),\n",
+    "    SVC(kernel='rbf')\n",
+    "    ),\n",
     "    # \"XGBoost\": XGBClassifier()\n",
     "}\n",
     "\n",