python - 分层KFold : IndexError: too many indices for array

Question

使用 sklearn 的 StratifiedKFold 函数，有人可以帮助我理解这里的错误吗？

我的猜测是它与我输入的标签数组有关，我注意到当我打印它们时(本例中的前 16 个)索引从 0 到 15，但是在我上面打印了一个额外的 0没想到。也许我只是一个 python 菜鸟，但这看起来很奇怪。

有人看到这里的错误吗？

文档:http://scikit-learn.org...StratifiedKFold.html

代码:

import nltk
import sklearn

print('The nltk version is {}.'.format(nltk.__version__))
print('The scikit-learn version is {}.'.format(sklearn.__version__))

print type(skew_gendata_targets.values), skew_gendata_targets.values.shape
print skew_gendata_targets.head(16)

skew_sfold10 = cross_validation.StratifiedKFold(skew_gendata_targets.values, n_folds=10, shuffle=True, random_state=20160121)

结果

The nltk version is 3.1.
The scikit-learn version is 0.17.
<type 'numpy.ndarray'> (500L, 1L)
    0
0   0
1   0
2   0
3   0
4   0
5   0
6   0
7   0
8   0
9   0
10  0
11  0
12  0
13  0
14  1
15  0
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-373-653b6010b806> in <module>()
      8 print skew_gendata_targets.head(16)
      9 
---> 10 skew_sfold10 = cross_validation.StratifiedKFold(skew_gendata_targets.values, n_folds=10, shuffle=True, random_state=20160121)
     11 
     12 #print '\nSkewed Generated Dataset (', len(skew_gendata_data), ')'

d:\Program Files\Anaconda2\lib\site-packages\sklearn\cross_validation.pyc in __init__(self, y, n_folds, shuffle, random_state)
    531         for test_fold_idx, per_label_splits in enumerate(zip(*per_label_cvs)):
    532             for label, (_, test_split) in zip(unique_labels, per_label_splits):
--> 533                 label_test_folds = test_folds[y == label]
    534                 # the test split can be too big because we used
    535                 # KFold(max(c, self.n_folds), self.n_folds) instead of

IndexError: too many indices for array

Answer 1

检查 skew_gendata_targets.values 的形状。您会看到它不是 StratifiedKFold 期望的一维数组(形状 (500,) )，而是 (500,1) 数组。 SKlearn 将它们分开处理，而不是强制它们相同。让我知道是否有帮助