Computational Thinking, Linear Algebra, Linear Regression, Python, Jupyter Notebook.
order='F') test_feat = np.zeros((len(y_test), n_feat), order='F') vec_poly(trn, trn_feat) vec_poly(test, test_feat) regr.fit(trn_feat, y_trn) LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False) regr_metrics(y_test, regr.predict(test_feat)) (55.74734592292935,