344a3d49e7c78300258fb4745c92b98ac57f38b1,skopt/learning/forest.py,ExtraTreesRegressor,predict,#ExtraTreesRegressor#,62

Before Change

            // This derives std(y | x) as described in 4.3.2 of arXiv:1211.0906
            std = np.zeros(len(X))

            for tree in self.estimators_:
                var_tree = tree.tree_.impurity[tree.apply(X)]
                mean_tree = tree.predict(X)
                std += var_tree + mean_tree ** 2

            std /= len(self.estimators_)
            std -= mean ** 2.0
            std[std < 0.0] = 0.0
            std = std ** 0.5

            return mean, std

        return mean

After Change

                raise ValueError(
                    "Expected impurity to be "mse", got %s instead"
                    % self.criterion)
            return mean, _return_std(X, self.estimators_, mean)

        return mean

Instances