#导入相关packages

from sklearn.model_selection import KFold

from sklearn.model_selection import StratifiedKFold

 1 import numpy as np

 2 from sklearn.model_selection import StratifiedKFold

 3 X = np.array([[1, 2], [3, 4], [1, 2], [3, 4]])

 4 y = np.array([0, 0, 1, 1])

 5 skf = StratifiedKFold(n_splits=2)

 6 skf.get_n_splits(X, y)

 7 >>>2

 8 print(skf)

 9 StratifiedKFold(n_splits=2, random_state=None, shuffle=False)

10 for train_index, test_index in skf.split(X, y):

11     print("TRAIN:", train_index, "TEST:", test_index)

12     X_train, X_test = X[train_index], X[test_index]    #返回数据框的方法 X_train = X.iloc[train_index]

13     y_train, y_test = y[train_index], y[test_index]

14 >>>TRAIN: [1 3] TEST: [0 2] #返回的是索引

15 >>>TRAIN: [0 2] TEST: [1 3]