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Exp/74 exp cross dataset validation #107

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nuluh merged 3 commits from exp/74-exp-cross-dataset-validation into dev 2025-08-28 05:09:16 +00:00
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@@ -862,17 +862,19 @@
"import matplotlib.pyplot as plt\n", "import matplotlib.pyplot as plt\n",
"from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\n", "from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\n",
"\n", "\n",
"# Create a figure with subplots\n",
"fig, axes = plt.subplots(1, 2, figsize=(12, 5))\n",
"\n", "\n",
"cm = confusion_matrix(y, y_pred_svm_1) # -> ndarray\n", "# Calculate confusion matrix\n",
"cm_A = confusion_matrix(y, y_pred_svm_1)\n",
"\n", "\n",
"# get the class labels\n", "# Get class labels\n",
"labels = svm_model.classes_\n", "labels = svm_model.classes_\n",
"\n", "\n",
"# Plot\n", "# Plot confusion matrix in first subplot\n",
"disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=labels)\n", "disp_A = ConfusionMatrixDisplay(confusion_matrix=cm_A, display_labels=labels)\n",
"disp.plot(cmap=plt.cm.Blues) # You can change colormap\n", "disp_A.plot(ax=axes[0], cmap=plt.cm.Blues)\n",
"plt.title(\"Confusion Matrix of Sensor A Test on Dataset B\")\n", "axes[0].set_title(\"Sensor A\")"
"plt.show()"
] ]
}, },
{ {
@@ -888,20 +890,26 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"svm_model = load('D:/thesis/models/sensor2/SVM.joblib')\n", "# svm_model = load('D:/thesis/models/sensor2/SVM.joblib')\n",
"# svm_model = load('D:/thesis/models/sensor2/SVM with StandardScaler and PCA.joblib')\n", "svm_model = load('D:/thesis/models/sensor2/SVM with StandardScaler and PCA.joblib')\n",
"y_pred_svm_2 = svm_model.predict(X2b)\n", "y_pred_svm_2 = svm_model.predict(X2b)\n",
"\n", "\n",
"# 5. Evaluate\n", "# 5. Evaluate\n",
"print(\"Accuracy on Dataset B:\", accuracy_score(y, y_pred_svm_2))\n", "\n",
"print(classification_report(y, y_pred_svm_2))" "df = pd.DataFrame(classification_report(y, y_pred_svm_2, output_dict=True)).T\n",
"# Round numbers nicely and move 'accuracy' into a row that fits your desired layout\n",
"df_rounded = df.round(2)\n",
"\n",
"# Export to LaTeX\n",
"latex_table = df_rounded.to_latex(index=True, float_format=\"%.2f\", caption=\"Classification report on Dataset B\", label=\"tab:clf_report_auto\")\n",
"print(latex_table)"
] ]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### Confusion Matrix Sensor B" "#### Confusion Matrix Sensor A and B"
] ]
}, },
{ {