Question

我正在尝试对分组数据实施交叉验证方案。我希望使用GroupKFold方法，但我一直收到错误。我究竟做错了什么？代码（与我使用的代码略有不同 - 我有不同的数据，所以我有一个更大的n_splits，但其他每一个都是相同的）

from sklearn import metrics
import matplotlib.pyplot as plt
import numpy as np
from sklearn.model_selection import GroupKFold
from sklearn.grid_search import GridSearchCV
from xgboost import XGBRegressor
#generate data
x=np.array([0,1,2,3,4,5,6,7,8,9,10,11,12,13])
y= np.array([1,2,3,4,5,6,7,1,2,3,4,5,6,7])
group=np.array([1,0,1,1,2,2,2,1,1,1,2,0,0,2)]
#grid search
gkf = GroupKFold( n_splits=3).split(x,y,group)
subsample = np.arange(0.3,0.5,0.1)
param_grid = dict( subsample=subsample)
rgr_xgb = XGBRegressor(n_estimators=50)
grid_search = GridSearchCV(rgr_xgb, param_grid, cv=gkf, n_jobs=-1)
result = grid_search.fit(x, y)

错误：

Traceback (most recent call last):

File "<ipython-input-143-11d785056a08>", line 8, in <module>
result = grid_search.fit(x, y)

File "/home/student/anaconda/lib/python3.5/site-packages/sklearn/grid_search.py", line 813, in fit
return self._fit(X, y, ParameterGrid(self.param_grid))

 File "/home/student/anaconda/lib/python3.5/site-packages/sklearn/grid_search.py", line 566, in _fit
n_folds = len(cv)

TypeError: object of type 'generator' has no len()

更改行

gkf = GroupKFold( n_splits=3).split(x,y,group)

到

gkf = GroupKFold( n_splits=3)

也不起作用。然后是错误消息：

'GroupKFold' object is not iterable

Answer 1

GroupKFold 的split函数产生训练和测试索引一次一对。您应该在拆分值上调用list以将它们全部放入列表中，以便计算长度：

gkf = list(GroupKFold( n_splits=3).split(x,y,group))

Sklearn：对分组数据进行交叉验证

1 个答案: