[英]Split dataset into 5~fold for cross-validation
我有一個數據集，我想將其拆分為 5 折（不同），而不是傳統的80-20拆分。
例如：
X = pd.DataFrame({'a': [1, 3, 5, 7, 4, 5, 6, 4, 7, 9],
'b': [3, 5, 6, 2, 4, 6, 7, 8, 7, 8],
'c': [2, 3, 4, 5, 6, 7, 8, 9, 2, 1]} )
y = [2, 3, 1, 1, 3, 2, 1, 3, 2, 2]
X
a b c
0 1 3 2
1 3 5 3
2 5 6 4
3 7 2 5
4 4 4 6
5 5 6 7
6 6 7 8
7 4 8 9
8 7 7 2
9 9 8 1
所以我有X1,X2,..,X5和相應的y1,y2,..,y5 。
使用KFold的sklearn ：
from sklearn.model_selection import KFold
print(list(kf.split(X, y)))
# Output:
[(array([2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1])),
(array([0, 1, 4, 5, 6, 7, 8, 9]), array([2, 3])),
(array([0, 1, 2, 3, 6, 7, 8, 9]), array([4, 5])),
(array([0, 1, 2, 3, 4, 5, 8, 9]), array([6, 7])),
(array([0, 1, 2, 3, 4, 5, 6, 7]), array([8, 9]))]
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