a3a539ed60af074ea3459835c788c2e900f3d8c1,mlxtend/classifier/stacking_cv_classification.py,StackingCVClassifier,predict_meta_features,#StackingCVClassifier#Any#,335

Before Change

        for model in self.clfs_:
            if not self.use_probas:
                single_model_prediction = model.predict(X)
                single_model_prediction = single_model_prediction\
                    .reshape(single_model_prediction.shape[0], 1)
            else:
                single_model_prediction = model.predict_proba(X)
            all_model_predictions = np.hstack((all_model_predictions.
                                               astype(single_model_prediction
                                                      .dtype),
                                               single_model_prediction))
        return all_model_predictions

    def predict(self, X):
         Predict target values for X.

After Change

        
        check_is_fitted(self, ["clfs_", "meta_clf_"])

        per_model_preds = []

        for model in self.clfs_:
            if not self.use_probas:
                prediction = model.predict(X)[:, np.newaxis]
            else:
                prediction = model.predict_proba(X)

            per_model_preds.append(prediction)

        return np.hstack(per_model_preds)

    def _stack_first_level_features(self, X, meta_features):
        if sparse.issparse(X):
            stack_fn = sparse.hstack

Instances