'Add additional ``n_estimators`` entries to all attributes.'

def _resize_state(self):

    total_n_estimators = self.n_estimators
    if (total_n_estimators < self.estimators_.shape[0]):
        raise ValueError(('resize    with    smaller    n_estimators    %d    <    %d' % (total_n_estimators, self.estimators_[0])))
    self.estimators_.resize((total_n_estimators, self.loss_.K))
    self.train_score_.resize(total_n_estimators)
    if ((self.subsample < 1) or hasattr(self, 'oob_improvement_')):
        if hasattr(self, 'oob_improvement_'):
            self.oob_improvement_.resize(total_n_estimators)
        else:
            self.oob_improvement_ = np.zeros((total_n_estimators,), dtype=np.float64)
