evaluate average runtime of a model

model_runtime.py

def test_model(model, sample, k=5):
    """
    get the mean time it takes to train the model over k-folds
    
    """
    x = sample.copy()  # set our predictors
    y = x.pop('y')  # set our response
    mean_fit_time = np.mean(cross_validate(model, x, y, cv=k)['fit_time']) * 100  # get mean run time

    return mean_fit_time