84dd314904ba2004ab35bbea65c5f2cb684e073c,autosklearn/estimators.py,AutoSklearnClassifier,predict,#AutoSklearnClassifier#Any#,273

Before Change

            predicted_classes.append(output_predicted_classes)

        prediction = np.vstack(predicted_classes)
        if self._n_outputs > 1:
            prediction = prediction.transpose()
        else:
            prediction = prediction.flatten()

        return prediction

    def predict_proba(self, X):
        Predict probabilities of classes for all samples X.

After Change

        
        predicted_indexes = super(AutoSklearnClassifier, self).predict(X)
        if self._n_outputs == 1:
            predicted_classes = self._classes[0].take(predicted_indexes)

            return predicted_classes
        else:
            n_samples = predicted_indexes.shape[0]
            predicted_classes = np.zeros((n_samples, self._n_outputs), dtype=object)

            for k in six.moves.range(self._n_outputs):
                output_predicted_indexes = predicted_indexes[:, k]
                predicted_classes[:, k] = self._classes[k].take(output_predicted_indexes)

            return predicted_classes

    def predict_proba(self, X):
        Predict probabilities of classes for all samples X.

        Parameters

Instances