class UseXGBoost(AdaClassifier):
def __init__(self, params):
self.xgboost = XGBoost(params)
self.tr_ids, self.tr_pred, self.tr_act = [], [], []
def train(self, tr_all, v_all, weights):
ids, pred, act = self.xgboost.train_clf(tr_all, v_all, weights)
self.tr_ids = ids
self.tr_pred = pred
self.tr_act = act
def get_labels(self):
return self.tr_ids, self.tr_pred, self.tr_act
def get_test_results(self, ts_data):
ts_ids, test_x = ts_data
return ts_ids, self.xgboost.test_clf(test_x)
class UseXGBoost(AdaClassifier):
def __init__(self,params):
self.xgboost = XGBoost(params)
self.tr_ids,self.tr_pred,self.tr_act = [],[],[]
def train(self,tr_all,v_all,weights):
ids, pred, act = self.xgboost.train_clf(tr_all,v_all,weights)
self.tr_ids = ids
self.tr_pred = pred
self.tr_act = act
def get_labels(self):
return self.tr_ids,self.tr_pred,self.tr_act
def get_test_results(self,ts_data):
ts_ids, test_x = ts_data
return ts_ids,self.xgboost.test_clf(test_x)
def __init__(self, params):
self.xgboost = XGBoost(params)
self.tr_ids, self.tr_pred, self.tr_act = [], [], []
def __init__(self,params):
self.xgboost = XGBoost(params)
self.tr_ids,self.tr_pred,self.tr_act = [],[],[]
