我在尝试构建一个XGBoost二元分类模型。我设置了训练和测试数据，并执行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            )

当我运行这段代码时，我得到了以下错误消息：

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_fD:\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:aftObjective candidate: binary:hingeObjective candidate: multi:softmaxObjective candidate: multi:softprobObjective candidate: rank:pairwiseObjective candidate: rank:ndcgObjective candidate: rank:mapObjective candidate: count:poissonObjective candidate: survival:coxObjective candidate: reg:gammaObjective candidate: reg:tweedieObjective candidate: reg:squarederrorObjective candidate: reg:squaredlogerrorObjective candidate: reg:logisticObjective candidate: reg:pseudohubererrorObjective candidate: binary:logisticObjective candidate: binary:logitrawObjective candidate: reg:linear

请问有人能解释一下这是怎么回事吗？我该如何修复这个错误？我使用的是Jupyter Notebook和Python 3，并使用了最新的XGB库版本。

回答：

从'binary:logistic'中移除空格应该就能解决问题。根据这个文档，中间没有空格。