from sklearn.metrics import accuracy_score, classification_report | |
def evaluate_model(model, X_test, y_test): | |
""" | |
Evaluate the trained model on the test set. | |
Args: | |
model: Trained model. | |
X_test (pd.DataFrame): Testing features. | |
y_test (pd.Series): Testing labels. | |
Returns: | |
dict: Evaluation metrics. | |
""" | |
y_pred = model.predict(X_test) | |
accuracy = accuracy_score(y_test, y_pred) | |
report = classification_report(y_test, y_pred) | |
return {"accuracy": accuracy, "classification_report": report} | |