StratifiedKFold 用法
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StratifiedKFold 用法
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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)
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