StratifiedKFold 將X_train和 X_test 做有放回抽樣，隨機(jī)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]))]

總結(jié)

以上是生活随笔為你收集整理的StratifiedKFold 用法的全部?jī)?nèi)容，希望文章能夠幫你解決所遇到的問(wèn)題。

如果覺(jué)得生活随笔網(wǎng)站內(nèi)容還不錯(cuò)，歡迎將生活随笔推薦給好友。