def test_correct_fit_date(self, X_y): base_model = LinearRegression() feature_splitter = FeatureSplitter() x, y = X_y[0], X_y[1] x_train, y_train, x_test, y_test = feature_splitter.transform(x, y) gar_no_feedforward = GAR(estimator=base_model) gar_no_feedforward.fit(x_train, y_train) predictions = gar_no_feedforward.predict(x_test) assert len(predictions) == len(x_test) np.testing.assert_array_equal(predictions.index, x_test.index) gar_with_feedforward = GARFF(estimator=base_model) gar_with_feedforward.fit(x_train, y_train) predictions = gar_with_feedforward.predict(x_test) assert len(predictions) == len(x_test) np.testing.assert_array_equal(predictions.index, x_test.index)
def _split_train_test(self, X: pd.DataFrame, y: pd.DataFrame): feature_splitter = FeatureSplitter() return feature_splitter.transform(X, y)
def _split_train_test(self, X, y): feature_splitter = FeatureSplitter() return feature_splitter.transform(X, y)