def test_two_estimators_predict_proba1(self): pipeline = StandardScaler() >> ( PCA() & Nystroem() & PassiveAggressiveClassifier() ) >> ConcatFeatures() >> NoOp() >> PassiveAggressiveClassifier() pipeline.fit(self.X_train, self.y_train) with self.assertRaises(ValueError): pipeline.predict_proba(self.X_test)
def test_two_estimators_predict_proba(self): pipeline = StandardScaler() >> ( PCA() & Nystroem() & LogisticRegression() ) >> ConcatFeatures() >> NoOp() >> LogisticRegression() pipeline.fit(self.X_train, self.y_train) pipeline.predict_proba(self.X_test)