def test_feature_importances_regressor():
"""Test feature_importances of Regressor class."""
regressor = Regressor()
with pytest.raises(ValueError):
regressor.feature_importances()
df_train = pd.read_csv("data_for_tests/clean_train.csv")
y_train = pd.read_csv("data_for_tests/clean_target.csv", squeeze=True)
regressor.set_params(strategy="LightGBM")
regressor.fit(df_train, y_train)
importance = regressor.feature_importances()
assert importance != {}
regressor.set_params(strategy="Linear")
regressor.fit(df_train, y_train)
importance = regressor.feature_importances()
assert importance != {}
regressor.set_params(strategy="RandomForest")
regressor.fit(df_train, y_train)
importance = regressor.feature_importances()
assert importance != {}
regressor.set_params(strategy="AdaBoost")
regressor.fit(df_train, y_train)
importance = regressor.feature_importances()
assert importance != {}
regressor.set_params(strategy="Bagging")
regressor.fit(df_train, y_train)
importance = regressor.feature_importances()
assert importance != {}
def test_fit_regressor():
"""Test fit method of Regressor class."""
df_train = pd.read_csv("data_for_tests/clean_train.csv")
y_train = pd.read_csv("data_for_tests/clean_target.csv", squeeze=True)
regressor = Regressor()
regressor.fit(df_train, y_train)
assert np.all(regressor._Regressor__col == df_train.columns)
assert regressor._Regressor__fitOK
def test_predict_regressor():
"""Test predict method of Regressor class."""
df_train = pd.read_csv("data_for_tests/clean_train.csv")
y_train = pd.read_csv("data_for_tests/clean_target.csv", squeeze=True)
regressor = Regressor()
with pytest.raises(ValueError):
regressor.predict(df_train)
regressor.fit(df_train, y_train)
with pytest.raises(ValueError):
regressor.predict(None)
assert len(regressor.predict(df_train)) > 0
def test_score_regressor():
"""Test_score method of Regressor class."""
df_train = pd.read_csv("data_for_tests/clean_train.csv")
y_train = pd.read_csv("data_for_tests/clean_target.csv", squeeze=True)
regressor = Regressor(strategy="Linear")
with pytest.raises(ValueError):
regressor.score(df_train, y_train)
regressor.fit(df_train, y_train)
with pytest.raises(ValueError):
regressor.score(None, y_train)
with pytest.raises(ValueError):
regressor.score(df_train, None)
assert regressor.score(df_train, y_train) > 0