01e68e64b745ebc5ef4a3b8c52e2ee9f3cac4cfb,mla/ensemble/random_forest.py,RandomForestRegressor,_predict,#RandomForestRegressor#Any#,70

Before Change

        predictions = np.zeros(X.shape[0])

        for i in range(X.shape[0]):
            row_pred = sum([tree.classify(X[i, :]) for tree in self.trees])
            row_pred /= self.n_estimators
            predictions[i] = row_pred
        return predictions

After Change

    def _predict(self, X=None):
        predictions = np.zeros((X.shape[0], self.n_estimators))
        for i, tree in enumerate(self.trees):
            predictions[:, i] = tree.predict(X)
        return predictions.mean(axis=1)

Instances