Implementation – GBDTEstimator class
field/method type/return type description
def __init__(self, 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