models.py 文件源码

def fit(self, X, y):
        if self.use_mspe:
            lgb_train = lgb.Dataset(X, y,
                        weight=np.ones(X.shape[0]), 
                        free_raw_data=False)
            lgb_test = lgb.Dataset(X, y, reference=lgb_train,
                        weight=np.ones(X.shape[0]), 
                        free_raw_data=False)
            self.gbm = lgb.train(
                self.kwargs,
                lgb_train,
                num_boost_round=10,
                fobj=mspe,
                feval=evalerror_lgbm,
                valid_sets=lgb_test)
        else:
            X_train, X_test, y_train, y_test = train_test_split(
                X, y, test_size=0.3)
            #lgb_test = lgb.Dataset(X, y, reference=lgb_train,
            #            weight=np.ones(X.shape[0]), 
            #            free_raw_data=False) 
            self.gbm.fit(X, y, early_stopping_rounds=10, eval_set=[(X, y)], verbose=False)
            #print "gbm best_iteration=", self.gbm.best_iteration