有几个类似的问题，但我找不到一个似乎适合的解决方案。我正在使用LightGBM和Scikit-Optimize的BayesSearchCV。
full_pipeline = skl.Pipeline(steps=[('preprocessor', pre_processor), ('estimator', lgbm.sklearn.LGBMClassifier())])scorer=make_scorer(fl.lgb_focal_f1_score)lgb_tuner = sko.BayesSearchCV(full_pipeline, hyper_space, cv=5, refit=True, n_iter=num_calls,scoring=scorer)lgb_tuner.fit(balanced_xtrain, balanced_ytrain)训练运行了一段时间后，出现了以下错误：
Traceback (most recent call last): File "/var/training.py", line 134, in <module> lgb_tuner.fit(balanced_xtrain, balanced_ytrain) File "/usr/local/lib/python3.6/site-packages/skopt/searchcv.py", line 694, in fit groups=groups, n_points=n_points_adjusted File "/usr/local/lib/python3.6/site-packages/skopt/searchcv.py", line 579, in _step self._fit(X, y, groups, params_dict) File "/usr/local/lib/python3.6/site-packages/skopt/searchcv.py", line 423, in _fit for parameters in parameter_iterable File "/usr/local/lib/python3.6/site-packages/joblib/parallel.py", line 1041, in __call__ if self.dispatch_one_batch(iterator): File "/usr/local/lib/python3.6/site-packages/joblib/parallel.py", line 859, in dispatch_one_batch self._dispatch(tasks) File "/usr/local/lib/python3.6/site-packages/joblib/parallel.py", line 777, in _dispatch job = self._backend.apply_async(batch, callback=cb) File "/usr/local/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 208, in apply_async result = ImmediateResult(func) File "/usr/local/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 572, in __init__ self.results = batch() File "/usr/local/lib/python3.6/site-packages/joblib/parallel.py", line 263, in __call__ for func, args, kwargs in self.items] File "/usr/local/lib/python3.6/site-packages/joblib/parallel.py", line 263, in <listcomp> for func, args, kwargs in self.items] File "/usr/local/lib/python3.6/site-packages/sklearn/model_selection/_validation.py", line 531, in _fit_and_score estimator.fit(X_train, y_train, **fit_params) File "/usr/local/lib/python3.6/site-packages/sklearn/pipeline.py", line 335, in fit self._final_estimator.fit(Xt, y, **fit_params_last_step) File "/usr/local/lib/python3.6/site-packages/lightgbm/sklearn.py", line 857, in fit callbacks=callbacks, init_model=init_model) File "/usr/local/lib/python3.6/site-packages/lightgbm/sklearn.py", line 617, in fit callbacks=callbacks, init_model=init_model) File "/usr/local/lib/python3.6/site-packages/lightgbm/engine.py", line 252, in train booster.update(fobj=fobj) File "/usr/local/lib/python3.6/site-packages/lightgbm/basic.py", line 2467, in update return self.__boost(grad, hess) File "/usr/local/lib/python3.6/site-packages/lightgbm/basic.py", line 2503, in __boost ctypes.byref(is_finished))) File "/usr/local/lib/python3.6/site-packages/lightgbm/basic.py", line 55, in _safe_call raise LightGBMError(decode_string(_LIB.LGBM_GetLastError()))lightgbm.basic.LightGBMError: 检查失败：(best_split_info.left_count) > (0) at /__w/1/s/python-package/compile/src/treelearner/serial_tree_learner.cpp, line 651 .一些类似问题的回答建议可能是由于使用GPU引起的，但我没有可用的GPU。我不知道还有什么原因导致这个问题，或者如何尝试修复它。有人能提供建议吗？
回答：
我认为这是由于我的超参数限制设置错误，导致一个不应该被设置为零的超参数被设置为零了，尽管我不确定是哪一个。
