如何解决回溯和未知 objective 函数的 XGBoost 错误？

Question

我正在尝试构建 XGBoost 二元分类模型。我设置了我的训练和测试数据并执行了以下操作以将数据拟合到模型中。

clf_xgb = xgb.XGBClassifier(objective = 'binary: logistic', missing = None, seed = 42)
clf_xgb.fit(X_train,
            y_train,
            eval_set = [(X_test, y_test)],
            eval_metric = 'aucpr',
            early_stopping_rounds=10,
            verbose = True
            )

当我运行此代码时，我收到以下错误消息：

XGBoostError                              Traceback (most recent call last)
<ipython-input-32-2a6f36907545> in <module>
----> 1 clf_xgb.fit(X_train, 
      2             y_train,
      3             eval_set = [(X_test, y_test)],
      4             eval_metric = 'aucpr',
      5             early_stopping_rounds=10,

D:\Softwares\anaconda\lib\site-packages\xgboost\core.py in inner_f(*args, **kwargs)
    434         for k, arg in zip(sig.parameters, args):
    435             kwargs[k] = arg
--> 436         return f(**kwargs)
    437 
    438     return inner_f

D:\Softwares\anaconda\lib\site-packages\xgboost\sklearn.py in fit(self, X, y, sample_weight, base_margin, eval_set, eval_metric, early_stopping_rounds, verbose, xgb_model, sample_weight_eval_set, base_margin_eval_set, feature_weights, callbacks)
   1174         )
   1175 
-> 1176         self._Booster = train(
   1177             params,
   1178             train_dmatrix,

D:\Softwares\anaconda\lib\site-packages\xgboost\training.py in train(params, dtrain, num_boost_round, evals, obj, feval, maximize, early_stopping_rounds, evals_result, verbose_eval, xgb_model, callbacks)
    187     Booster : a trained booster model
    188     """
--> 189     bst = _train_internal(params, dtrain,
    190                           num_boost_round=num_boost_round,
    191                           evals=evals,

D:\Softwares\anaconda\lib\site-packages\xgboost\training.py in _train_internal(params, dtrain, num_boost_round, evals, obj, feval, xgb_model, callbacks, evals_result, maximize, verbose_eval, early_stopping_rounds)
     74             show_stdv=False, cvfolds=None)
     75 
---> 76     bst = callbacks.before_training(bst)
     77 
     78     for i in range(start_iteration, num_boost_round):

D:\Softwares\anaconda\lib\site-packages\xgboost\callback.py in before_training(self, model)
    374         '''Function called before training.'''
    375         for c in self.callbacks:
--> 376             model = c.before_training(model=model)
    377             msg = 'before_training should return the model'
    378             if self.is_cv:

D:\Softwares\anaconda\lib\site-packages\xgboost\callback.py in before_training(self, model)
    513 
    514     def before_training(self, model):
--> 515         self.starting_round = model.num_boosted_rounds()
    516         return model
    517 

D:\Softwares\anaconda\lib\site-packages\xgboost\core.py in num_boosted_rounds(self)
   2005         rounds = ctypes.c_int()
   2006         assert self.handle is not None
-> 2007         _check_call(_LIB.XGBoosterBoostedRounds(self.handle, ctypes.byref(rounds)))
   2008         return rounds.value
   2009 

D:\Softwares\anaconda\lib\site-packages\xgboost\core.py in _check_call(ret)
    208     """
    209     if ret != 0:
--> 210         raise XGBoostError(py_str(_LIB.XGBGetLastError()))
    211 
    212 

XGBoostError: [12:05:23] C:\Users\Administrator\workspace\xgboost-win64_release_1.4.0\src\objective\objective.cc:26: Unknown objective function: `binary: logistic`
Objective candidate: survival:aft
Objective candidate: binary:hinge
Objective candidate: multi:softmax
Objective candidate: multi:softprob
Objective candidate: rank:pairwise
Objective candidate: rank:ndcg
Objective candidate: rank:map
Objective candidate: count:poisson
Objective candidate: survival:cox
Objective candidate: reg:gamma
Objective candidate: reg:tweedie
Objective candidate: reg:squarederror
Objective candidate: reg:squaredlogerror
Objective candidate: reg:logistic
Objective candidate: reg:pseudohubererror
Objective candidate: binary:logistic
Objective candidate: binary:logitraw
Objective candidate: reg:linear

谁能解释一下这是怎么回事。我该如何解决这个错误？我正在使用 Jupyter Notebook 和 Python 3 并使用最新的 XGB 库版本。

Answer 1

从 'binary:logistic' 中删除 space，它应该可以工作。根据此 this 文档，两者之间没有 space。

如何解决回溯和未知 objective 函数的 XGBoost 错误？

How to solve XGBoost error for traceback and unknown objective function?

classification

machine-learning

xgbclassifier