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- from sklearn.ensemble import BaggingClassifier
- from sklearn.tree import DecisionTreeClassifier
- from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
- # Create Bagging classifier with Decision Tree as base estimator
- bagging_model = BaggingClassifier(
- base_estimator=DecisionTreeClassifier(),
- n_estimators=50,
- random_state=42
- )
- # Train the model
- bagging_model.fit(X_train_scaled, y_train)
- # Predict
- y_pred_bagging = bagging_model.predict(X_test_scaled)
- # Evaluate
- print("Bagging with Decision Tree")
- print("Accuracy:", accuracy_score(y_test, y_pred_bagging))
- print(confusion_matrix(y_test, y_pred_bagging))
- print(classification_report(y_test, y_pred_bagging))
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