6bf1dd3ada59f67c91c815a31d440de61632220e,src/skmultiflow/trees/hoeffding_tree.py,HoeffdingTree,partial_fit,#HoeffdingTree#Any#Any#Any#Any#,887

Before Change

            self.classes = classes
        if y is not None:
            if weight is None:
                weight = np.array([1.0])
            row_cnt, _ = get_dimensions(X)
            wrow_cnt, _ = get_dimensions(weight)
            if row_cnt != wrow_cnt:
                weight = [weight[0]] * row_cnt
            for i in range(row_cnt):
                if weight[i] != 0.0:
                    self._train_weight_seen_by_model += weight[i]
                    self._partial_fit(X[i], y[i], weight[i])

    def _partial_fit(self, X, y, weight):

After Change

        if y is not None:
            row_cnt, _ = get_dimensions(X)
            if weight is None:
                weight = np.ones(row_cnt)
            if row_cnt != len(weight):
                raise ValueError("Inconsistent number of instances ({}) and weights ({}).".format(row_cnt, len(weight)))
            for i in range(row_cnt):
                if weight[i] != 0.0:
                    self._train_weight_seen_by_model += weight[i]
                    self._partial_fit(X[i], y[i], weight[i])

Instances