def test_default_metric_getter_works_as_expected_regressor(self):
linreg = Model(LinearRegression())
assert linreg.config.CLASSIFIER_METRIC == "accuracy"
assert linreg.config.REGRESSION_METRIC == "r2"
assert linreg.default_metric == "r2"
linreg.default_metric = "neg_mean_squared_error"
assert linreg.config.CLASSIFIER_METRIC == "accuracy"
assert linreg.config.REGRESSION_METRIC == "neg_mean_squared_error"
assert linreg.default_metric == "neg_mean_squared_error"
linreg.config.reset_config()
def test_default_metric_getter_works_as_expected_classifier(self):
rf = Model(RandomForestClassifier(n_estimators=10))
assert rf.config.CLASSIFIER_METRIC == "accuracy"
assert rf.config.REGRESSION_METRIC == "r2"
assert rf.default_metric == "accuracy"
rf.default_metric = "fowlkes_mallows_score"
assert rf.config.CLASSIFIER_METRIC == "fowlkes_mallows_score"
assert rf.config.REGRESSION_METRIC == "r2"
assert rf.default_metric == "fowlkes_mallows_score"
rf.config.reset_config()
