自然语言处理_样本处理_Stratified k-fold

Stratified k-fold
StratifiedKFold is a variation of k-fold which returns stratified folds: each set contains approximately the same percentage of samples of each target class as the complete set.

from sklearn.model_selection import StratifiedKFold, KFold
import numpy as np
X, y = np.ones((50, 1)), np.hstack(([0] * 45, [1] * 5))

skf = StratifiedKFold(n_splits=3)
for train, test in skf.split(X, y):
    print('train -  {}   |   test -  {}'.format(
        np.bincount(y[train]), np.bincount(y[test])))

kf = KFold(n_splits=3)
for train, test in kf.split(X, y):
    print('train -  {}   |   test -  {}'.format(
        np.bincount(y[train]), np.bincount(y[test])))

Stratified 表示分层,是在k折的基础上增加了分层的约束
简单理解是分层k折抽样