#NEWLINE# def test_regression_big( ) : #NEWLINE# #INDENT# ( X , y ) = make_regression ( n_samples = 200000 , n_features = 10 , n_informative = 5 , noise = 30.0 , random_state = 0 ) #NEWLINE# X = pd . DataFrame ( X ) #NEWLINE# y = pd . Series ( y ) #NEWLINE# cls = MALSS ( 'regression' ) . fit ( X , y , 'test_regression_big' ) #NEWLINE# cls . generate_module_sample ( ) #NEWLINE# from sklearn.metrics import mean_squared_error #NEWLINE# pred = cls . predict ( X ) #NEWLINE# print ( mean_squared_error ( y , pred ) ) #NEWLINE# assert ( len ( cls . algorithms ) == 1 ) #NEWLINE# assert ( cls . algorithms [ 0 ] . best_score is not None )