print # <codecell> params = clf.get_params() params # <codecell> test_score = np.zeros((params['n_estimators'],), dtype=np.float64) test_score # <codecell> for i, y_pred in enumerate(clf.staged_decision_function(X_test)): test_score[i] = clf.loss_(y_test, y_pred) test_score # <codecell> plt.figure(figsize=(12, 6)) plt.subplot(1, 2, 1) plt.title('Deviance') plt.plot(np.arange(params['n_estimators']) + 1, clf.train_score_, 'b-', label='Training Set Deviance') plt.plot(np.arange(params['n_estimators']) + 1, test_score, 'r-', label='Test Set Deviance') plt.legend(loc='upper right') plt.xlabel('Boosting Iterations') plt.ylabel('Deviance')