update

ad_xgboost_train.py

@@ -24,7 +24,7 @@ xgb_model = XGBClassifier(
     objective='binary:logistic',
     learning_rate=0.3,
     max_depth=10,
-    eval_metric=['error', 'logloss']
+    eval_metric=['error', 'logloss', 'auc']
 )
 xgb_model.fit(x_train, y_train, eval_set=[(x_train, y_train), (x_test, y_test)])
 # 5. 模型保存