sklearn.model_selection "KFold" 对象不可迭代

Question

我对以下代码有问题

这是代码

# simulate splitting a dataset of 25 observations into 5 folds
from sklearn.model_selection import KFold
kf = KFold(n_splits=5, random_state=None, shuffle=False)
# print the contents of each training and testing set
print('{} {:^61} {}'.format('Iteration', 
                            'Training set observations', 
                            'Testing set observations'))
for iteration, data in enumerate(kf, start=1):
    print('{:^9} {} {!s:^25}'.format(iteration, data[0], data[1]))

类型错误："KFold"对象不可迭代

TypeError                                 Traceback (most recent call last)
<ipython-input-21-13995db0f7c7> in <module>()
        5 # print the contents of each training and testing set
        6 print('{} {:^61} {}'.format('Iteration', 'Training set 
observations', 'Testing set observations'))
  ----> 7 for iteration, data in enumerate(kf, start=1):
        8     print('{:^9} {} {!s:^25}'.format(iteration, data[0], data[1]))
TypeError: 'KFold' object is not iterable

Answer 1

类 "cross_validation" 中有一个参数 "y"（要拆分为 K 折叠的样本）：

类sklearn.cross_validation。StratifiedKFold（y， n_folds=3， shuffle=False， random_state=None）[source]

这个参数对我来说还不够model_selection

# simulate splitting a dataset of 25 observations into 5 folds
from sklearn.model_selection import KFold
kf = KFold(n_splits=5, random_state=None, shuffle=False)
Vec = np.arange(0,26)
# print the contents of each training and testing set
print('{} {:^61} {}'.format('Iteration', 
                            'Training set observations', 
                            'Testing set observations'))
for iteration, data in enumerate(kf.split(Vec), start=1):
   print('{:^9} {} {!s:^25}'.format(iteration, data[0], data[1]))