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

Before Change

        
        check_is_fitted(self, "clfs_")
        all_model_predictions = np.array([]).reshape(len(X), 0)
        for model in self.clfs_:
            if not self.use_probas:
                single_model_prediction = model.predict(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