文章目录
1 系统聚类及可视化
运行代码:
w=read.csv("E://mvstats5/data/LA.Neighborhoods.csv")#读入数据
w=data.frame(w,density=w$Population/w$Area)#增加人口密度变量
u=w[,c(1,2,5,6,11,16)]#选择变量
hw=hclust(dist(scale(u[,-1])), "ward.D2") #对标准化的数据做分层聚类, 聚类方法选的"ward.D2"
plot(hw,labels=u[,1],cex=0.6)#画树状图
id=identify(hw)#手工分成5份
rect.hclust(hw,5)
运行结果:
2 KMeans聚类及可视化
运行代码:
a=kmeans(scale(u[,-1]),5);ppp=c(7,17,19,21)
plot(w[a$cluster==1,14:15],pch=1,col=1,xlim=c(-118.7,-118.2),ylim=c(33.73,34.32),main="Los Angeles")
for(i in 2:5){
points(w[a$cluster==i,14:15],pch=ppp[i-1],col=2:5)
legend("bottomleft",pch=c(1,ppp),paste("Cluster",1:4))
}
运行结果: