n_samples= 1000n_outliers= 50X, y, coef = datasets.make_regression(n_samples=n_samples, n_features=1, n_informative=1, noise=10, coef=True, random_state=0)#Add outlier datanp.random.seed(0) X[:n_outliers]= 3 + 0.5 * np.random.normal(size=(n_outliers, 1)) y[:n_outliers]= ...