737adbe4855d116648cc47f583e3cc258b35187c,src/skmultiflow/classification/trees/regression_hoeffding_tree.py,RegressionHoeffdingTree,predict,#RegressionHoeffdingTree#Any#,170

Before Change

            votes = self.get_votes_for_instance(X[i]).copy()
            if votes == {}:
                // Tree is empty, all target_values equal, default to zero
                predictions.append([0])
            else:
                number_of_examples_seen = votes[0]
                sum_of_values = votes[1]
                predictions.append(sum_of_values / number_of_examples_seen)

After Change

                normalized_sample = self.normalize_sample(X[i])
                normalized_prediction = np.dot(self.get_weights_for_instance(X[i]), normalized_sample)
                mean = self.sum_of_values / self.examples_seen
                sd = np.sqrt((self.sum_of_squares - self.sum_of_values ** 2
                          / self.examples_seen) / self.examples_seen)
                if self.examples_seen > 1:
                    predictions.append(normalized_prediction * sd * 3 + mean)
                else:
                    predictions.append(0)

Instances