N_OUTLIERS = 25 X, y, coef = datasets.make_regression( n_samples=N_SAMPLES, n_features=1, n_informative=1, noise=20, coef=True, random_state=42 ) coef_list = [["original_coef", float(coef)]] # add outliers np.random.seed(42) X[:N_OUTLIERS] = 10 + 0.75 * np.random.normal...