python - 当我通过 early_stopping_rounds 时 XGBClassifier 失败

Question

我按以下方式使用 xgboost:

from xgboost import XGBClassifier
clf = XGBClassifier()
clf = clf.fit(df_train, df_train_labels, verbose=True)

这很好用。但是，如果我添加一个 early_stopping_rounds 参数，如下所示:

clf = clf.fit(df_train, df_train_labels, early_stopping_rounds=10, verbose=True)

我收到这个错误:

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-16-786925228ae5> in <module>()
      9 
     10 
---> 11 clf = clf.fit(df_train, df_train_labels, early_stopping_rounds=10, verbose=True)
     12 print("after fit")
     13 prediction = np.exp(clf.predict(df_test))

~/anaconda3/envs/python3/lib/python3.6/site-packages/xgboost/sklearn.py in fit(self, X, y, sample_weight, eval_set, eval_metric, early_stopping_rounds, verbose)
    443                               early_stopping_rounds=early_stopping_rounds,
    444                               evals_result=evals_result, obj=obj, feval=feval,
--> 445                               verbose_eval=verbose)
    446 
    447         self.objective = xgb_options["objective"]

~/anaconda3/envs/python3/lib/python3.6/site-packages/xgboost/training.py in train(params, dtrain, num_boost_round, evals, obj, feval, maximize, early_stopping_rounds, evals_result, verbose_eval, learning_rates, xgb_model, callbacks)
    203                            evals=evals,
    204                            obj=obj, feval=feval,
--> 205                            xgb_model=xgb_model, callbacks=callbacks)
    206 
    207 

~/anaconda3/envs/python3/lib/python3.6/site-packages/xgboost/training.py in _train_internal(params, dtrain, num_boost_round, evals, obj, feval, xgb_model, callbacks)
     99                                end_iteration=num_boost_round,
    100                                rank=rank,
--> 101                                evaluation_result_list=evaluation_result_list))
    102         except EarlyStopException:
    103             break

~/anaconda3/envs/python3/lib/python3.6/site-packages/xgboost/callback.py in callback(env)
    190     def callback(env):
    191         """internal function"""
--> 192         score = env.evaluation_result_list[-1][1]
    193         if len(state) == 0:
    194             init(env)

IndexError: list index out of range

我查了一下，发现 fit 方法可以传递大量参数，所以我认为我添加 early_stopping_rounds 的事实不应该造成问题。

知道这个错误的原因是什么吗？

Answer 1

出现此错误的原因是您没有指定 eval_set，xgboost 使用该 eval_set 来确定何时停止以进行提前停止。

请参阅有关fit 方法的文档 here .

eval_set (list, optional) – A list of (X, y) tuple pairs to use as a validation set for early-stopping

例如，如果您将数据分成训练集和测试集，您可以使用以下方法:

eval_set = [(X_test, y_test)]

clf = clf.fit(df_train,
              df_train_labels,
              eval_set=eval_set,
              early_stopping_rounds=10,
              verbose=True)