numpy用于shuffle训练集数据

import numpy as np

W_train = [1,2,3]
R_train = [4,5,6]
Y_train = [7,8,9]
L_train = [10,11,12]

data_train = [(w, r, y, l) for w, r, y, l in zip(W_train, R_train, Y_train, L_train)]

np.random.shuffle(data_train)
print(data_train )
W_train = [w for w, r, y, l in data_train]
R_train = [r for w, r, y, l in data_train]
Y_train = [y for w, r, y, l in data_train]
L_train = [l for w, r, y, l in data_train]
print((W_train, R_train, Y_[(2, 5, 8, 11), (3, 6, 9, 12), (1, 4, 7, 10)]
([2, 3, 1], [5, 6, 4], [8, 9, 7], [11, 12, 10]), L_train))
exit()

输出为

[(2, 5, 8, 11), (3, 6, 9, 12), (1, 4, 7, 10)]
([2, 3, 1], [5, 6, 4], [8, 9, 7], [11, 12, 10])
保证了(w, r, y, l)这几个相互对应的值是一起被调整顺序的。

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转载自blog.csdn.net/listep/article/details/79758202