聚类分析有很多种， 效果好不好大概要根据数据特征来确定。最常见的是kmeans法聚类

>setwd("D:\\R_test")>data_in<-read.delim("tmp_result.txt",header=T)>fit<-kmeans(data_in,3)>library(cluster)>clusplot(data_in,fit$cluster,color=T,shade=T,labels=2,lines=0)

也可以用mclust

>install.packages("mclust")试开URL’http://cloud.r-project.org/bin/windows/contrib/2.14/mclust_4.0.zip'Contenttype'application/zip'length2371233bytes(2.3Mb)打开了URLdownloaded2.3Mb程序包‘mclust’打开成功，MD5和检查也通过下载的程序包在C:\Users\Administrator\AppData\Local\Temp\RtmpiIyw2o\downloaded_packages里>fit<-Mclust(data_in)>summary(fit)----------------------------------------------------GaussianfinitemixturemodelfittedbyEMalgorithm----------------------------------------------------MclustXXX(elliposidalmultivariatenormal)modelwith1component:log.likelihoodndfBIC1616504263334103046843Clusteringtable:1263>fit$//按下Tab键，有以下选项fit$callfit$modelNamefit$nfit$dfit$Gfit$BICfit$bicfit$loglikfit$dffit$parametersfit$classificationfit$uncertainty>plot(fit,what="classification")//http://www.statmethods.net/advstats/cluster.html