StratifiedKFold 用法

StratifiedKFold 將X_train和 X_test 做有放回抽樣，隨機分三次，取出索引

import numpy as np
from sklearn.model_selection import StratifiedKFold
X = np.array([[1, 2], [3, 4], [1, 2], [3, 4]])
y = np.array([0, 0, 1, 1])
skf = StratifiedKFold(n_splits=2).split(X, y)
#c= skf.get_n_splits(X, y)

for train_index, test_index in skf:
     print("TRAIN:", train_index, "TEST:", test_index)
     X_train, X_test = X[train_index], X[test_index]
     y_train, y_test = y[train_index], y[test_index]

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

import numpy as np
from sklearn.model_selection import StratifiedKFold
X = np.array([[1, 2], [3, 4], [1, 2], [3, 4]])
y = np.array([0, 0, 1, 1])
skf = StratifiedKFold(n_splits=2).split(X, y)

print(list(skf))

[(array([1, 3]), array([0, 2])), (array([0, 2]), array([1, 3]))]