sklearn Pipeline：“ColumnTransformer”类型的参数不可迭代

Posted 2023-03-12

【中文标题】sklearn Pipeline：“ColumnTransformer”类型的参数不可迭代

【英文标题】：sklearn Pipeline: argument of type 'ColumnTransformer' is not iterable

【发布时间】：2020-09-16 14:42:18

【问题描述】：

我正在尝试使用管道来为集成投票分类器提供数据，因为我希望集成学习器使用在不同特征集上训练的模型。为此，我遵循了[1] 上的教程。

以下是我目前可以开发的代码。

y = df1.index
x = preprocessing.scale(df1)

phy_features = ['A', 'B', 'C']
phy_transformer = Pipeline(steps=[('imputer', SimpleImputer(strategy='median')), ('scaler', StandardScaler())])
phy_processer = ColumnTransformer(transformers=[('phy', phy_transformer, phy_features)])

fa_features = ['D', 'E', 'F']
fa_transformer = Pipeline(steps=[('imputer', SimpleImputer(strategy='median')), ('scaler', StandardScaler())])
fa_processer = ColumnTransformer(transformers=[('fa', fa_transformer, fa_features)])


pipe_phy = Pipeline(steps=[('preprocessor', phy_processer ),('classifier', SVM)])
pipe_fa = Pipeline(steps=[('preprocessor', fa_processer ),('classifier', SVM)])

ens = VotingClassifier(estimators=[pipe_phy, pipe_fa])

cv = KFold(n_splits=10, random_state=None, shuffle=True)
for train_index, test_index in cv.split(x):
    x_train, x_test = x[train_index], x[test_index]
    y_train, y_test = y[train_index], y[test_index]
    ens.fit(x_train,y_train)
    print(ens.score(x_test, y_test))

但是，在运行代码时，我在ens.fit(x_train,y_train) 行收到一条错误消息TypeError: argument of type 'ColumnTransformer' is not iterable。

以下是我收到的完整堆栈跟踪。

Traceback (most recent call last):
  File "<input>", line 1, in <module>
  File "C:\Program Files\JetBrains\PyCharm 2020.1.1\plugins\python\helpers\pydev\_pydev_bundle\pydev_umd.py", line 197, in runfile
    pydev_imports.execfile(filename, global_vars, local_vars)  # execute the script
  File "C:\Program Files\JetBrains\PyCharm 2020.1.1\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "C:/Users/ASUS/PycharmProjects/swelltest/enemble.py", line 112, in <module>
    ens.fit(x_train,y_train)
  File "C:\Users\ASUS\PycharmProjects\swelltest\venv\lib\site-packages\sklearn\ensemble\_voting.py", line 265, in fit
    return super().fit(X, transformed_y, sample_weight)
  File "C:\Users\ASUS\PycharmProjects\swelltest\venv\lib\site-packages\sklearn\ensemble\_voting.py", line 65, in fit
    names, clfs = self._validate_estimators()
  File "C:\Users\ASUS\PycharmProjects\swelltest\venv\lib\site-packages\sklearn\ensemble\_base.py", line 228, in _validate_estimators
    self._validate_names(names)
  File "C:\Users\ASUS\PycharmProjects\swelltest\venv\lib\site-packages\sklearn\utils\metaestimators.py", line 77, in _validate_names
    invalid_names = [name for name in names if '__' in name]
  File "C:\Users\ASUS\PycharmProjects\swelltest\venv\lib\site-packages\sklearn\utils\metaestimators.py", line 77, in <listcomp>
    invalid_names = [name for name in names if '__' in name]
TypeError: argument of type 'ColumnTransformer' is not iterable

以下是发生错误时名称列表中的值。

1- ColumnTransformer(transformers=[('phy',
                                 Pipeline(steps=[('imputer',
                                                  SimpleImputer(strategy='median')),
                                                 ('scaler', StandardScaler())]),
                                 ['HR', 'RMSSD', 'SCL'])])
2- ColumnTransformer(transformers=[('fa',
                                 Pipeline(steps=[('imputer',
                                                  SimpleImputer(strategy='median')),
                                                 ('scaler', StandardScaler())]),
                                 ['Squality', 'Sneutral', 'Shappy'])])

这是什么原因，我该如何解决？

【参考方案1】：

VotingClassifier 的 estimators 参数应该是对（名称、估计器）的列表，例如

ens = VotingClassifier(estimators=[('phy', pipe_phy),
                                   ('fa', pipe_fa)])

（在您的代码中，检查试图找到该对的第二个元素，因此抱怨ColumnTransformer 不可迭代。）

【参考方案2】：

我确实设法使用变通方法让代码运行，这有点难看。

该库似乎正在尝试搜索 ColumnTransform 对象的“__”子字符串，但它无法执行。

由于此名称检查对我的功能没有显着影响，我在sklearn\utils\metaestimators.py 评论了以下 sn-p。

invalid_names = [name for name in names if '__' in name]
if invalid_names:
    raise ValueError('Estimator names must not contain __: got '
                    '0!r'.format(invalid_names))