def __init__(self, train_x, train_y, valid_x, valid_y, names=None, weight=None, init_train_score=None, init_valid_score=None): if type(weight) == int: train_x, train_y = data_copy(train_x, train_y, weight) weight = None self.dtrain = xgb.DMatrix(train_x, train_y, feature_names=names, weight=weight) self.dvalid = xgb.DMatrix(valid_x, valid_y, feature_names=names) self.model = None self.names = names
def __init__(self, train_x, train_y, valid_x, valid_y, names=None, weight=None): print('weight :', weight) if type(weight) == int: print('copy datas') train_x, train_y = data_copy(train_x, train_y, weight) self.dtrain = (train_x, train_y) self.dvalid = (valid_x, valid_y) self.feature_names = names self.model = None
def __init__(self, train_x, train_y, valid_x, valid_y, names=None, weight=None, init_train_score=None, init_valid_score=None): if type(weight) == int: train_x, train_y = data_copy(train_x, train_y, weight) weight = None self.dtrain = lgb.Dataset(train_x, train_y, feature_name=names, weight=weight, init_score=init_train_score) self.dvalid = lgb.Dataset(valid_x, valid_y, feature_name=names, init_score=init_valid_score) self.feature_names = names self.model = None