瑞士卷聚类-kmeans

瑞士卷聚类

from mpl_toolkits.mplot3d import Axes3D

from sklearn.cluster import KMeans

from sklearn import manifold, datasets

import matplotlib.pyplot as plt

#生成带噪声的瑞士卷数据集

X,color = datasets.samples_generator.make_swiss_roll(n_samples=1500)

#使用100个K-means簇对数据进行近似

clusters_swiss_roll = KMeans(n_clusters=100,random_state=1).fit_predict(X)

fig2 = plt.figure()

ax = fig2.add_subplot(111,projection='3d')

ax.scatter(X[:,0],X[:,1],X[:,2],c = clusters_swiss_roll,cmap = 'Spectral')

plt.show()