Esempio n. 1
0
def test_cross_validate(toy_data):

    # First test with a specified CV iterator.
    current_dir = os.path.dirname(os.path.realpath(__file__))
    folds_files = [(current_dir + '/custom_train',
                    current_dir + '/custom_test')]

    reader = Reader(line_format='user item rating', sep=' ', skip_lines=3)
    data = Dataset.load_from_folds(folds_files=folds_files, reader=reader,
                                   rating_scale=(1, 5))

    algo = NormalPredictor()
    pkf = ms.PredefinedKFold()
    ret = ms.cross_validate(algo, data, measures=['rmse', 'mae'], cv=pkf,
                            verbose=1)
    # Basically just test that keys (dont) exist as they should
    assert len(ret['test_rmse']) == 1
    assert len(ret['test_mae']) == 1
    assert len(ret['fit_time']) == 1
    assert len(ret['test_time']) == 1
    assert 'test_fcp' not in ret
    assert 'train_rmse' not in ret
    assert 'train_mae' not in ret

    # Test that 5 fold CV is used when cv=None
    # Also check that train_* key exist when return_train_measures is True.
    ret = ms.cross_validate(algo, toy_data, measures=['rmse', 'mae'], cv=None,
                            return_train_measures=True, verbose=True)
    assert len(ret['test_rmse']) == 5
    assert len(ret['test_mae']) == 5
    assert len(ret['fit_time']) == 5
    assert len(ret['test_time']) == 5
    assert len(ret['train_rmse']) == 5
    assert len(ret['train_mae']) == 5
Esempio n. 2
0
def test_cross_validate():

    # First test with a specified CV iterator.
    current_dir = os.path.dirname(os.path.realpath(__file__))
    folds_files = [(current_dir + '/custom_train',
                    current_dir + '/custom_test')]

    reader = Reader(line_format='user item rating',
                    sep=' ',
                    skip_lines=3,
                    rating_scale=(1, 5))
    data = Dataset.load_from_folds(folds_files=folds_files, reader=reader)

    algo = NormalPredictor()
    pkf = ms.PredefinedKFold()
    ret = ms.cross_validate(algo,
                            data,
                            measures=['rmse', 'mae'],
                            cv=pkf,
                            verbose=1)
    assert len(ret['test_rmse']) == 1
    assert len(ret['test_mae']) == 1
    assert len(ret['fit_time']) == 1
    assert len(ret['test_time']) == 1
    assert 'test_fcp' not in ret

    # Test that 5 fold CV is used when cv=None
    data = Dataset.load_from_file(current_dir + '/custom_dataset', reader)
    ret = ms.cross_validate(algo, data, measures=['rmse', 'mae'], cv=None)
    assert len(ret['test_rmse']) == 5
    assert len(ret['test_mae']) == 5
    assert len(ret['fit_time']) == 5
    assert len(ret['test_time']) == 5