Learning Curves Plotting function

val_curve_params.py

def val_curve_params(model, X, y, param_name, param_range, scoring = 'roc_auc', cv = 10):
    train_score, test_score = validation_curve(
    model, X = X, y = y, param_name = param_name, param_range = param_range, scoring = scoring, cv = cv)
    
    mean_train_score = np.mean(train_score, axis = 1)
    mean_test_score = np.mean(test_score, axis = 1)
    
    plt.plot(param_range, mean_train_score,
            label = 'Training Score', color = 'b')
    plt.plot(param_range, mean_test_score,
            label = 'Validation Score', color = 'g')
    
    plt.title(f'Validation Curve for {type(model).__name__}')
    plt.xlabel(f'Number of {param_name}')
    plt.ylabel(f'{scoring}')
    plt.tight_layout()
    plt.legend(loc = 'best')
    plt.show(block = True)
    
# Example: val_curve_params(random_forest, X, y, 'max_depth', range(1, 11), scoring = 'roc_auc')