擅长:python、mysql、java
<p>我想,你可以用<a href="https://en.wikipedia.org/wiki/Cosine_similarity" rel="nofollow noreferrer"><strong>Cosine similarity</strong></a>表示给定向量和给定矩阵之间的距离。找到abs不是一个好方法,因为数据不是标准化的。你知道吗</p>
<pre><code> import numpy as np
from numpy import dot
from numpy.linalg import norm
a = np.array([[0.85,717,0.06,24.0],[0.49,718,2.87,23.0],[0.28,876,0.00,4.0],[21.40,353,2.34,528.0],[23.24,371,2.79,674.0]])
b = np.array([56,2200,130,8])
cos_sim = dot(a, b)/(norm(a)*norm(b))
selected_row = np.argmin(cos_sim) + 1
print ("Distances:")
print (cos_sim)
print ("Selected_row: " + str(selected_row))
</code></pre>