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