How to implement Mahalanobis distance in Python
This time I will bring you PythonHow to implement the Mahalanobis distance, what are the precautions for implementing the Mahalanobis distance algorithm in Python, the following is a practical case, let's take a look.
The example in this article describes the calculation of Mahalanobis distance algorithm implemented in Python. Share it with everyone for your reference, the details are as follows:
I wrote the function and called
python to implement the Mahalanobis distance source code :
# encoding: utf-8
from future import pision
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import numpy as np
def mashi_distance(x,y):
print x
print y
#马氏距离要求样本数要大于维数，否则无法求协方差矩阵
#此处进行转置，表示10个样本，每个样本2维
X=np.vstack([x,y])
print X
XT=X.T
print XT
#方法一：根据公式求解
S=np.cov(X) #两个维度之间协方差矩阵
SI = np.linalg.inv(S) #协方差矩阵的逆矩阵
#马氏距离计算两个样本之间的距离，此处共有4个样本，两两组合，共有6个距离。
n=XT.shape[0]
d1=[]
for i in range(0,n):
for j in range(i+1,n):
delta=XT[i]-XT[j]
d=np.sqrt(np.dot(np.dot(delta,SI),delta.T))
print d
d1.append(d)
if name == 'main':
# 第一列
x = [3, 5, 2, 8]
# 第二列
y = [4, 6, 2, 4]
mashi_distance(x,y)Running results:
# I believe you have mastered the method after reading the case in this article. For more exciting information, please pay attention to other related articles on the PHP Chinese website!
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The above is the detailed content of How to implement Mahalanobis distance in Python. For more information, please follow other related articles on the PHP Chinese website!
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