def test_with_incompatible_estimator_1(self):
trainable_pipeline = IsolationForest()
trained_pipeline = trainable_pipeline.fit(self.X_train, self.y_train)
with self.assertRaises(AttributeError):
_ = trained_pipeline.predict_log_proba(self.X_test)
def test_score_samples_trained_trainable(self):
clf = IsolationForest()
clf.fit(self.X_train)
with self.assertWarns(DeprecationWarning):
clf.score_samples(self.X_test)
def test_with_no_y(self):
clf = IsolationForest()
trained = clf.fit(self.X_train)
trained.predict(self.X_test)
def test_score_samples(self):
clf = IsolationForest()
trained = clf.fit(self.X_train)
trained.score_samples(self.X_test)