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