分组K折交叉验证：sklearn.model_selection.GroupKFold(n_splits=3)
参数说明：
n_splits：折数，默认为3，至少为2
注意点：同一组的样本不可能同时出现在同一折的测试集和训练集中。
①数据集均等份，且每组中的样本也是均等
In [11]: from sklearn.model_selection import GroupKFold ...: import numpy as np ...: X = np.arange(24).reshape(12,2) ...: y = np.array([1,1,2,3,1,2,3,2,2,3,3,1]) ...: groups = np.array([1,2,3,4,5,6,1,2,3,4,5,6]) ...: kf = GroupKFold(n_splits=6) ...: for train_index , test_index in kf.split(X,y,groups): ...: print('train_index:%s , test_index: %s ' %(train_index,test_index) ...: ) ...: print('train_groups:%s , test_groups: %s ' %(groups[train_index],g ...: roups[test_index])) ...: train_index:[ 0 1 2 3 4 6 7 8 9 10] , test_index: [ 5 11] train_groups:[1 2 3 4 5 1 2 3 4 5] , test_groups: [6 6] train_index:[ 0 1 2 3 5 6 7 8 9 11] , test_index: [ 4 10] train_groups:[1 2 3 4 6 1 2 3 4 6] , test_groups: [5 5] train_index:[ 0 1 2 4 5 6 7 8 10 11] , test_index: [3 9] train_groups:[1 2 3 5 6 1 2 3 5 6] , test_groups: [4 4] train_index:[ 0 1 3 4 5 6 7 9 10 11] , test_index: [2 8] train_groups:[1 2 4 5 6 1 2 4 5 6] , test_groups: [3 3] train_index:[ 0 2 3 4 5 6 8 9 10 11] , test_index: [1 7] train_groups:[1 3 4 5 6 1 3 4 5 6] , test_groups: [2 2] train_index:[ 1 2 3 4 5 7 8 9 10 11] , test_index: [0 6] train_groups:[2 3 4 5 6 2 3 4 5 6] , test_groups: [1 1]②折数均等，组数不平衡 In [13]: #sklearn.model_selection.GroupKFold(n_splits=3) ...: from sklearn.model_selection import GroupKFold ...: import numpy as np ...: X = np.arange(24).reshape(12,2) ...: y = np.array([1,1,2,3,1,2,3,2,2,3,3,1]) ...: groups = np.array([1,2,3,4,5,6,1,2,3,4,5,7]) ...: kf = GroupKFold(n_splits=4) ...: for train_index , test_index in kf.split(X,y,groups): ...: print('train_index:%s , test_index: %s ' %(train_index,test_index) ...: ) ...: print('train_groups:%s , test_groups: %s ' %(groups[train_index],g ...: roups[test_index])) ...: train_index:[ 1 2 3 5 7 8 9 11] , test_index: [ 0 4 6 10] train_groups:[2 3 4 6 2 3 4 7] , test_groups: [1 5 1 5] train_index:[ 0 1 2 4 5 6 7 8 10] , test_index: [ 3 9 11] train_groups:[1 2 3 5 6 1 2 3 5] , test_groups: [4 4 7] train_index:[ 0 1 3 4 6 7 9 10 11] , test_index: [2 5 8] train_groups:[1 2 4 5 1 2 4 5 7] , test_groups: [3 6 3] train_index:[ 0 2 3 4 5 6 8 9 10 11] , test_index: [1 7] train_groups:[1 3 4 5 6 1 3 4 5 7] , test_groups: [2 2]③折数不均等，组数不平衡 In [14]: from sklearn.model_selection import GroupKFold ...: import numpy as np ...: X = np.arange(24).reshape(12,2) ...: y = np.array([1,1,2,3,1,2,3,2,2,3,3,1]) ...: groups = np.array([1,2,3,4,5,6,1,2,3,4,5,3]) ...: kf = GroupKFold(n_splits=5) ...: for train_index , test_index in kf.split(X,y,groups): ...: print('train_index:%s , test_index: %s ' %(train_index,test_index) ...: ) ...: print('train_groups:%s , test_groups: %s ' %(groups[train_index],g ...: roups[test_index])) ...: train_index:[ 0 1 3 4 5 6 7 9 10] , test_index: [ 2 8 11] train_groups:[1 2 4 5 6 1 2 4 5] , test_groups: [3 3 3] train_index:[ 0 1 2 3 6 7 8 9 11] , test_index: [ 4 5 10] train_groups:[1 2 3 4 1 2 3 4 3] , test_groups: [5 6 5] train_index:[ 0 1 2 4 5 6 7 8 10 11] , test_index: [3 9] train_groups:[1 2 3 5 6 1 2 3 5 3] , test_groups: [4 4] train_index:[ 0 2 3 4 5 6 8 9 10 11] , test_index: [1 7] train_groups:[1 3 4 5 6 1 3 4 5 3] , test_groups: [2 2] train_index:[ 1 2 3 4 5 7 8 9 10 11] , test_index: [0 6] train_groups:[2 3 4 5 6 2 3 4 5 3] , test_groups: [1 1]