就是这个代码：
from sklearn import datasets
from sklearn.cluster import AgglomerativeClustering
import matplotlib.pyplot as plt
from sklearn.metrics import confusion_matrix
import pandas as pd
iris = datasets.load_iris()
irisdata = iris.data
clustering = AgglomerativeClustering(linkage='ward', n_clusters=3)
res = clustering.fit(irisdata)
print "各个簇的样本数目："
print pd.Series(clustering.labels_).value_counts()
print "聚类结果："
print confusion_matrix(iris.target,clustering.labels_)
plt.figure()
d0 = irisdata[clustering.labels_==0]
plt.plot(d0[:,0],d0[:,1],'r.')
d1 = irisdata[clustering.labels_==1]
plt.plot(d1[:,0],d1[:,1],'go')
d2 = irisdata[clustering.labels_==2]
plt.plot(d2[:,0],d2[:,1],'b*')
plt.xlabel("Sepal.Length")
plt.ylabel("Sepal.Width")
plt.title("AGNES Clustering")
plt.show()
#输出：
#各个簇的样本数目：
#0 64
#1 50
#dtype: int64
#聚类结果：
#[[ 0 50 0]