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我正在使用 GridSearchCV 来查找 PLS-DA 模型（偏最小二乘判别分析）的最佳参数（组件数）。

y_train是一个看起来像 [1111....0000] 的 np 数组，所以有两个类（0 和 1）。班级是平衡的。

但是，当我运行此代码时，出现此错误（在： 行gd_sr.fit(X_train, y_train)）：“y_true 中仅存在一个类。在这种情况下未定义 ROC AUC 分数。” 看起来 python 没有在y_train.

谁能帮我这个？

# Selecting data (training set)

X_train=data.loc[:, 'v1':'v546'].values 
y_train=data['pregnancy']
y_train=np.where(y_train == 'Open',0,1)  

# Parameter tuning using 10-fold cross-validation

grid_param={'n_components':[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]}
gd_sr = GridSearchCV(estimator=PLSRegression(),
                     param_grid=grid_param,
                     scoring='roc_auc', 
                     cv=10,
                     n_jobs=-1) 

gd_sr.fit(X_train, y_train)

best_parameters = gd_sr.best_params_  # find the best parameter (number of components)
print(best_parameters)

best_result = gd_sr.best_score_ # accuracy with the best parameter
print(best_result)

这是完整的错误：


alueError                                Traceback (most recent call last)
<ipython-input-131-cd811da4b437> in <module>
     20                      n_jobs=-1) # -1 means that we use all available computing power (CPU)
     21 
---> 22 gd_sr.fit(X_train, y_train)
     23 
     24 best_parameters = gd_sr.best_params_  # find the best parameter (number of components)

~/.local/lib/python3.7/site-packages/sklearn/utils/validation.py in inner_f(*args, **kwargs)
     71                           FutureWarning)
     72         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 73         return f(**kwargs)
     74     return inner_f
     75 

~/.local/lib/python3.7/site-packages/sklearn/model_selection/_search.py in fit(self, X, y, groups, **fit_params)
    734                 return results
    735 
--> 736             self._run_search(evaluate_candidates)
    737 
    738         # For multi-metric evaluation, store the best_index_, best_params_ and

~/.local/lib/python3.7/site-packages/sklearn/model_selection/_search.py in _run_search(self, evaluate_candidates)
   1186     def _run_search(self, evaluate_candidates):
   1187         """Search all candidates in param_grid"""
-> 1188         evaluate_candidates(ParameterGrid(self.param_grid))
   1189 
   1190 

~/.local/lib/python3.7/site-packages/sklearn/model_selection/_search.py in evaluate_candidates(candidate_params)
    713                                for parameters, (train, test)
    714                                in product(candidate_params,
--> 715                                           cv.split(X, y, groups)))
    716 
    717                 if len(out) < 1:

~/.local/lib/python3.7/site-packages/joblib/parallel.py in __call__(self, iterable)
   1040 
   1041             with self._backend.retrieval_context():
-> 1042                 self.retrieve()
   1043             # Make sure that we get a last message telling us we are done
   1044             elapsed_time = time.time() - self._start_time

~/.local/lib/python3.7/site-packages/joblib/parallel.py in retrieve(self)
    919             try:
    920                 if getattr(self._backend, 'supports_timeout', False):
--> 921                     self._output.extend(job.get(timeout=self.timeout))
    922                 else:
    923                     self._output.extend(job.get())

~/.local/lib/python3.7/site-packages/joblib/_parallel_backends.py in wrap_future_result(future, timeout)
    540         AsyncResults.get from multiprocessing."""
    541         try:
--> 542             return future.result(timeout=timeout)
    543         except CfTimeoutError as e:
    544             raise TimeoutError from e

/usr/lib/python3.7/concurrent/futures/_base.py in result(self, timeout)
    430                 raise CancelledError()
    431             elif self._state == FINISHED:
--> 432                 return self.__get_result()
    433             else:
    434                 raise TimeoutError()

/usr/lib/python3.7/concurrent/futures/_base.py in __get_result(self)
    382     def __get_result(self):
    383         if self._exception:
--> 384             raise self._exception
    385         else:
    386             return self._result

ValueError: Only one class present in y_true. ROC AUC score is not defined in that case.

编辑：我用 Logistic Regression 尝试了 GridSearchCV 并且它可以工作（除了参数之外没有改变任何东西），所以问题可能来自 PLSRegression() 算法。

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