85cc5f10bbc3f06db3198e0b31c4d36f2d2d84c2,test/test_evaluation/test_holdout_evaluator.py,HoldoutEvaluatorTest,test_predict_proba_binary_classification,#HoldoutEvaluatorTest#,60

Before Change

                return np.array([[0.1, 0.9], [0.7, 0.3]])

        model = Dummy2()
        task_type = BINARY_CLASSIFICATION

        configuration_space = get_configuration_space(
            D.info,
            include_estimators=["extra_trees"],
            include_preprocessors=["select_rates"])
        configuration = configuration_space.sample_configuration()

        evaluator = HoldoutEvaluator(D, self.output_dir, configuration)
        pred = evaluator.predict_proba(None, model, task_type,
                                       D.data["Y_train"])
        expected = [[0.9], [0.3]]
        for i in range(len(expected)):
            self.assertEqual(expected[i], pred[i][1])

After Change

        evaluator = HoldoutEvaluator(D, self.output_dir, configuration)
        evaluator.model = model
        loss, Y_optimization_pred, Y_valid_pred, Y_test_pred = \
            evaluator.fit_predict_and_loss()

        for i in range(23):

Instances