def test_ada_boost_regressor(self):
from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
X, y = load_boston(return_X_y=True)
X_train, X_test, y_train, y_test = train_test_split(X, y)
from lale.lib.sklearn import AdaBoostRegressor, DecisionTreeRegressor
reg = AdaBoostRegressor(base_estimator = DecisionTreeRegressor())
trained = reg.auto_configure(X_train, y_train, optimizer=Hyperopt, max_evals=1, scoring='r2')
#Checking that the inner decision tree does not get the default value for min_samples_leaf, not sure if this will always pass
self.assertNotEqual(trained.hyperparams()['base_estimator'].hyperparams()['min_samples_leaf'], 1)
def test_ccp_alpha(self):
with self.assertRaisesRegex(jsonschema.ValidationError,
"argument 'ccp_alpha' was unexpected"):
_ = DecisionTreeRegressor(ccp_alpha=0.01)
def test_with_defaults(self):
trainable = DecisionTreeRegressor()
trained = trainable.fit(self.train_X, self.train_y)
_ = trained.predict(self.test_X)