def _init_state(self):

        if self.init is None:
            self.init_ = self.loss_.init_estimator()
        elif isinstance(self.init, six.string_types):
            self.init_ = INIT_ESTIMATORS[self.init]()
        else:
            self.init_ = self.init

        self.estimators_ = np.empty((self.n_estimators, self.loss_.K),
                                    dtype=np.object)
        self.train_score_ = np.zeros((self.n_estimators,), dtype=np.float64)
        # do oob?
        if self.subsample < 1.0:
            self.oob_improvement_ = np.zeros((self.n_estimators),
                                             dtype=np.float64)
Initialize model state and allocate model state data structures.
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/ensemble/gradient_boosting.py/BaseGradientBoosting._init_state