def METHOD_NAME(self):
    # Initialize factory
    factory = ParallelVigraRfLazyflowClassifierFactory(10, variable_importance_enabled=True)
    # Train
    classifier = factory.create_and_train(self.training_feature_matrix, self.training_labels)
    assert isinstance(classifier, ParallelVigraRfLazyflowClassifier)
    assert list(classifier.known_classes) == [1, 2]
    assert len(classifier.feature_names) == 2
    # Predict
    probabilities = classifier.predict_probabilities(self.prediction_data)
    assert probabilities.shape == (4, 2)
    assert probabilities.dtype == numpy.float32
    assert (0 <= probabilities).all() and (probabilities <= 1.0).all()
    assert (numpy.argmax(probabilities, axis=-1) + 1 == self.expected_classes).all()