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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# XGBoost with oversampled dataset evaluation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Probability Thresholds"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(0, 1)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"from sklearn.metrics import precision_recall_curve\n",
"\n",
"# Predict\n",
"y_scores_threshold = xgb_classif.predict_proba(X_test)[:,1]\n",
"\n",
"precision, recall, thresholds = precision_recall_curve(y_test, y_scores_threshold) \n",
"\n",
"#retrieve probability of being 1(in second column of probs_y)\n",
"pr_auc = metrics.auc(recall, precision)\n",
"\n",
"plt.title(\"Precision-Recall vs Threshold Chart\")\n",
"plt.plot(thresholds, precision[: -1], \"b--\", label=\"Precision\")\n",
"plt.plot(thresholds, recall[: -1], \"r--\", label=\"Recall\")\n",
"plt.ylabel(\"Precision, Recall\")\n",
"plt.xlabel(\"Threshold\")\n",
"plt.legend(loc=\"lower left\")\n",
"plt.ylim([0,1])"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"# XGBoost Classifier predict\n",
"\n",
"threshold = 0.5\n",
"\n",
"y_pred = np.where(xgb_classif.predict_proba(X_test)[:,1] > threshold, 1, 0)\n",
"y_scores = xgb_classif.predict_proba(X_test)[:,1]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### F1-score, precision and recall"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" 1 0.87 0.75 0.80 114393\n",
" 0 0.78 0.89 0.83 114124\n",
"\n",
" accuracy 0.82 228517\n",
" macro avg 0.82 0.82 0.82 228517\n",
"weighted avg 0.82 0.82 0.82 228517\n",
"\n"
]
}
],
"source": [
"from sklearn.metrics import classification_report\n",
"target_names = hardbounce_dummy['flgHardBounce_n'].astype('str').unique()\n",
"print(classification_report(y_test, y_pred, target_names=target_names))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Accuracy"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy: 0.817558431101406\n"
]
}
],
"source": [
"print(\"Accuracy:\",metrics.accuracy_score(y_test, y_pred))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot Confusion Matrix"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Normalized confusion matrix\n",
"[[0.74744084 0.25255916]\n",
" [0.1121587 0.8878413 ]]\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fa87eb06a90>"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"class_names = hardbounce_dummy['flgHardBounce_n'].astype('str').unique()\n",
"aux_functions.plot_confusion_matrix(y_test, y_pred, classes=class_names, cmap=plt.cm.Blues, normalize=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### AVG Precision Score"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"AVG Precision Score: 0.9009808638026707\n"
]
}
],
"source": [
"print(\"AVG Precision Score: \", metrics.average_precision_score(y_test, y_scores))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### AUC"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"AUC: 0.9043\n"
]
}
],
"source": [
"auc_metric = metrics.roc_auc_score(y_test, y_scores)\n",
"print(\"AUC: %.4f\" % auc_metric)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### ROC Curve"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"AUC: 0.9043\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fpr, tpr, auc_thresholds = metrics.roc_curve(y_test, y_scores)\n",
"print(\"AUC: %.4f\" % metrics.auc(fpr, tpr)) # AUC of ROC\n",
"aux_functions.plot_roc_curve(fpr, tpr, 'recall_optimized')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot XGB Tree"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"xgb.plot_tree(xgb_classif,num_trees=0)\n",
"plt.rcParams['figure.figsize'] = [100, 70]\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot Variable Importance"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"xgb.plot_importance(xgb_classif)\n",
"plt.rcParams['figure.figsize'] = [10, 10]\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"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": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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