利用sklearn库应用Kmeans方法对鸢尾花数据聚类

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from sklearn.cluster import KMeans
from sklearn import datasets
plt.rcParams[&＃39;font.sans-serif&＃39;]&＃61;[&＃39;SimHei&＃39;] #用来正常显示中文标签&＃xfffc;
plt.rcParams[&＃39;axes.unicode_minus&＃39;]&＃61;False #用来正常显示负号np.random.seed(5)
iris &＃61; datasets.load_iris()
X &＃61; iris.data
Y &＃61; iris.target
est &＃61; KMeans(n_clusters&＃61;3)
est.fit(X)
labels &＃61; est.labels_fig &＃61; plt.figure(1, figsize&＃61;(4, 3))
ax &＃61; Axes3D(fig, rect&＃61;[0, 0, .95, 1], elev&＃61;48, azim&＃61;134)
ax.scatter(X[:, 3], X[:, 0], X[:, 2],c&＃61;labels.astype(np.float), edgecolor&＃61;&＃39;k&＃39;)
ax.w_xaxis.set_ticklabels([])
ax.w_yaxis.set_ticklabels([])
ax.w_zaxis.set_ticklabels([])
ax.set_xlabel(&＃39;花瓣宽度&＃39;)
ax.set_ylabel(&＃39;萼片长度&＃39;)
ax.set_zlabel(&＃39;花瓣长度&＃39;)
ax.set_title("3类")
ax.dist &＃61; 12
plt.show()