使用python中的sklearn计算数据点和质心（kmeans）之间的距离

Question

我正在尝试使用sklearn的kmeans进行聚类。我需要计算每个数据点与其质心之间的距离。谁能在这里帮助我。

预先感谢

import re
import sys
import os
import sklearn.datasets
from sklearn.cluster import KMeans
dataFilename = sys.argv[1]
X, y = sklearn.datasets.load_svmlight_file(dataFilename)
kmeans = KMeans(n_clusters=3)
kmeans.fit(X)
centroids = kmeans.cluster_centers_
labels = kmeans.predict(X)
j=0
intervals = []
for i in range(0,max(labels)+1):
    intervals.append([])
print(intervals)
for i in y:
    intervals[labels[j]].append(int(y[j]))
    j += 1
print(intervals)