擅长:python、mysql、java
<p>可以在应用提取之前修复种子:</p>
<pre><code>import numpy as np
# Each labels correspond to the first element of each line of face_train
labels_train = np.array(range(0,15,3))
face_train = np.array(range(15)).reshape(5,3)
np.random.seed(0)
reduced_train_face = face_train[np.random.randint(face_train.shape[0], size=3), :]
np.random.seed(0)
reduced_train_labels = labels_train[np.random.randint(labels_train.shape[0], size=3)]
print(reduced_train_face, reduced_train_labels)
# [[12, 13, 14], [ 0, 1, 2], [ 9, 10, 11]], [12, 0, 9]
</code></pre>
<p>同样的种子,也会以同样的方式减少。在</p>
<p><strong>编辑</strong>:我建议您使用<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.choice.html" rel="nofollow noreferrer">^{<cd1>}</a>,以确保每个数据只选择一次而不是两次相同的数据</p>