params: dict): None initializer def calc_grad(self, y_true: np.ndarray [float, ndim=1], y_pred: np.ndarray [float, ndim=1]) Tuple[ np.ndarray [float, ndim=1], np.ndarray [float, ndim=1] ] calculate gradient and hessian from target and prediction (abstract method, implemented in Regressor/Classifier) def fit(self, x: np.ndarray[float, ndim=2], y: np.ndarray[float, ndim=1]): None train by constructing trees def predict(self, x: np.ndarray[float, ndim=2]) np.ndarray [float, ndim=1] predict with constructed trees