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 = [],[],[]