运行 gridsearchcv with pipeline 时出错

Question

我想创建一个包含模型训练过程中所有过程的流水线结构。做了相关的库和定义后，我创建了如下结构来实验。我使用了电信客户流失数据集。

ohe_f =["gender","SeniorCitizen","Partner","Dependents","PhoneService","MultipleLines",
    "InternetService","OnlineSecurity","OnlineBackup","DeviceProtection","TechSupport",
    "StreamingTV","StreamingMovies","Contract","PaperlessBilling","PaymentMethod"]

X_train, X_test, y_train, y_test = train_test_split(X,
                                                    y,
                                                    test_size=0.2,
                                                    stratify=y,
                                                    random_state=11)


pipeline = Pipeline(steps = [['smote', SMOTE(random_state=11)],
                             ['scaler', MinMaxScaler()],
                             ['encoder', OneHotEncoder(),ohe_f],
                             ['classifier', LogisticRegression(random_state=11)]])

stratified_kfold = StratifiedKFold(n_splits=3,
                                       shuffle=True,
                                       random_state=11)
    
param_grid = {'classifier__C':[0.01, 0.1, 1, 10, 100]}

grid_search = GridSearchCV(estimator=pipeline,
                           param_grid=param_grid,
                           scoring='roc_auc',
                           cv=stratified_kfold,
                           n_jobs=-1)

当我开始训练模型时，出现以下错误。我该如何解决？

---------------------------------------------------------------------------
_RemoteTraceback                          Traceback (most recent call last)
_RemoteTraceback: 
"""
Traceback (most recent call last):
  File "C:\Users\burak\anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 436, in _process_worker
    r = call_item()
  File "C:\Users\burak\anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 288, in __call__
    return self.fn(*self.args, **self.kwargs)
  File "C:\Users\burak\anaconda3\lib\site-packages\joblib\_parallel_backends.py", line 595, in __call__
    return self.func(*args, **kwargs)
  File "C:\Users\burak\anaconda3\lib\site-packages\joblib\parallel.py", line 262, in __call__
    return [func(*args, **kwargs)
  File "C:\Users\burak\anaconda3\lib\site-packages\joblib\parallel.py", line 262, in <listcomp>
    return [func(*args, **kwargs)
  File "C:\Users\burak\anaconda3\lib\site-packages\sklearn\utils\fixes.py", line 216, in __call__
    return self.function(*args, **kwargs)
  File "C:\Users\burak\anaconda3\lib\site-packages\sklearn\model_selection\_validation.py", line 668, in _fit_and_score
    estimator = estimator.set_params(**cloned_parameters)
  File "C:\Users\burak\anaconda3\lib\site-packages\sklearn\pipeline.py", line 188, in set_params
    self._set_params("steps", **kwargs)
  File "C:\Users\burak\anaconda3\lib\site-packages\sklearn\utils\metaestimators.py", line 54, in _set_params
    super().set_params(**params)
  File "C:\Users\burak\anaconda3\lib\site-packages\sklearn\base.py", line 239, in set_params
    valid_params = self.get_params(deep=True)
  File "C:\Users\burak\anaconda3\lib\site-packages\sklearn\pipeline.py", line 167, in get_params
    return self._get_params("steps", deep=deep)
  File "C:\Users\burak\anaconda3\lib\site-packages\sklearn\utils\metaestimators.py", line 33, in _get_params
    out.update(estimators)
ValueError: dictionary update sequence element #2 has length 3; 2 is required
"""

The above exception was the direct cause of the following exception:

ValueError                                Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_1388/1962240236.py in <module>
     23                            n_jobs=-1)
     24 
---> 25 grid_search.fit(X_train, y_train)
     26 cv_score = grid_search.best_score_
     27 test_score = grid_search.score(X_test, y_test)

~\anaconda3\lib\site-packages\sklearn\model_selection\_search.py in fit(self, X, y, groups, **fit_params)
    889                 return results
    890 
--> 891             self._run_search(evaluate_candidates)
    892 
    893             # multimetric is determined here because in the case of a callable

~\anaconda3\lib\site-packages\sklearn\model_selection\_search.py in _run_search(self, evaluate_candidates)
   1390     def _run_search(self, evaluate_candidates):
   1391         """Search all candidates in param_grid"""
-> 1392         evaluate_candidates(ParameterGrid(self.param_grid))
   1393 
   1394 

~\anaconda3\lib\site-packages\sklearn\model_selection\_search.py in evaluate_candidates(candidate_params, cv, more_results)
    836                     )
    837 
--> 838                 out = parallel(
    839                     delayed(_fit_and_score)(
    840                         clone(base_estimator),

~\anaconda3\lib\site-packages\joblib\parallel.py in __call__(self, iterable)
   1054 
   1055             with self._backend.retrieval_context():
-> 1056                 self.retrieve()
   1057             # Make sure that we get a last message telling us we are done
   1058             elapsed_time = time.time() - self._start_time

~\anaconda3\lib\site-packages\joblib\parallel.py in retrieve(self)
    933             try:
    934                 if getattr(self._backend, 'supports_timeout', False):
--> 935                     self._output.extend(job.get(timeout=self.timeout))
    936                 else:
    937                     self._output.extend(job.get())

~\anaconda3\lib\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

~\anaconda3\lib\concurrent\futures\_base.py in result(self, timeout)
    443                     raise CancelledError()
    444                 elif self._state == FINISHED:
--> 445                     return self.__get_result()
    446                 else:
    447                     raise TimeoutError()

~\anaconda3\lib\concurrent\futures\_base.py in __get_result(self)
    388         if self._exception:
    389             try:
--> 390                 raise self._exception
    391             finally:
    392                 # Break a reference cycle with the exception in self._exception

ValueError: dictionary update sequence element #2 has length 3; 2 is required

Answer 1

您需要将管道分成两部分：一个处理数字特征（使用最小最大缩放器），另一个处理分类特征（使用一个热编码器）。您可以使用 scikit-learn 中的 class ColumnTransformer ：https://scikit-learn.org/stable/auto_examples/compose/plot_column_transformer_mixed_types.html

运行 gridsearchcv with pipeline 时出错

Error when running gridsearchcv with pipeline

python

data-fitting

gridsearchcv