TypeError: __init__()得到了一个意外的关键字参数“shuffle”

I got this error while runing my code in python 2.6.6. And there is no issue while running in Python 3.4.3

在python 2.6.6中运行代码时，我得到了这个错误。在Python 3.4.3中运行时没有问题。

usr/lib64/python2.6/site-packages/sklearn/feature_selection/univariate_selection.py:319: UserWarning: Duplicate scores. Result may depend on feature ordering.There are probably duplicate features, or you used a classification score for a regression task.
      warn("Duplicate scores. Result may depend on feature ordering."
    Traceback (most recent call last):
      File "classification.py", line 31, in <module>
        main()
      File "classification.py", line 15, in main
        tm.optimaltrain(conf)
      File "/axp/gabm/npscnnct/dev/getThemes/textminer/textminer/classify.py", line 121, in optimaltrain
        score = self.cv(X,y,model)
      File "/axp/gabm/npscnnct/dev/getThemes/textminer/textminer/classify.py", line 140, in cv
        skf = cross_validation.StratifiedKFold(y, n_folds=self.cv_folds, shuffle=True)
    TypeError: __init__() got an unexpected keyword argument 'shuffle'

Code:

代码:

  def cv(self, X, y, model):
    y_true = []
    y_pred = []
    skf = cross_validation.StratifiedKFold(y, n_folds=self.cv_folds, shuffle=True)
    for train_index, test_index in skf:
      X_train, X_test = X[train_index], X[test_index]
      y_train, y_test = y[train_index], y[test_index]
      model.fit(X_train, y_train)
      y_pred += list(model.predict(X_test))
      y_true += list(y_test)

But when I remove the Shuffle=True from the code its runing fine. Modules I am using are scipy 0.11.0, nltk 2.0.1, sklearn 0.14.1

但是当我从代码中移除Shuffle=True时，它的运行良好。我使用的模块是scipy 0.11.0, nltk 2.0.1, sklearn 0.14.1。

Please advice. Thanks

请建议。谢谢

2 个解决方案

#1

Here is the source for your version (0.14) of sklearn: https://github.com/scikit-learn/scikit-learn/blob/0.14.X/sklearn/cross_validation.py#L391

这里是您的sklearn版本(0.14)的源代码:https://github.com/scikit-learn/scikitlearn/blob/0.14.x/sklearn/cross_valides.py #L391。

I've linked to the actual line for the init on StratifiedKFold - which shows that there is no shuffle keyword argument.

我已经将init的实际行链接到层fiedkfold上，这表明没有shuffle关键字参数。

Upgrade to v 0.15, which does have shuffle (as seen here: https://github.com/scikit-learn/scikit-learn/blob/0.15.X/sklearn/cross_validation.py#L399).

升级到v0.15，它确实有洗牌(如图所示:https://github.com/scikit-learn/scikit-learn/sclearn/cross_valides.py #L399)。

I'm going to assume that your version of sklearn on Py3 is 0.15?

假设Py3上的sklearn版本是0。15?

#2

In sklearn 0.14, cross_validation.StratifiedKFold() has no keyword argument shuffle. Apparently, it was only added in a later version (0.15 actually).

在sklearn 0.14中，cross_valid.层fiedkfold()没有关键字参数调整。显然，它只是在后来的版本中添加了(实际上是0.15)。

You can either update sklearn or shuffle the input yourself (eg. with random.shuffle()) before stratification.

你可以更新sklearn，也可以自己洗牌(如。与random.shuffle分层前())。

#1