Module 9.2 Boosting

from sklearn.ensemble import GradientBoostingClassifier

# Create Gradient Boosting model
boosting_model = GradientBoostingClassifier(n_estimators=100, random_state=42)

# Train the model
boosting_model.fit(X_train, y_train)  # Note: No scaling needed for trees

# Predict
y_pred_boosting = boosting_model.predict(X_test)

# Evaluate
print("Gradient Boosting")
print("Accuracy:", accuracy_score(y_test, y_pred_boosting))
print(confusion_matrix(y_test, y_pred_boosting))
print(classification_report(y_test, y_pred_boosting))