Hierarchy-based clustering----Agnes algorithm using (R language)

Condensation

# Generate DataSet X<-c (Rnorm (200,30,1), Rnorm (200,10,1.5), Rnorm (100,5,0.5)) y<-c (Rnorm (200,30,1), Rnorm (200,10,1.5), Rnorm (100,5,0.5)) data<-data.frame (x, y) # color space Library (colorspace) # shows the structure of the dataset str (data) # System Clustering # Some of the necessary functions of clustering library (CLU
ster) Library (rattle) #系统聚类函数在包amap中 require (AMAP, quietly=true) #聚类结果有包fpc提供 require (FPC, quietly=true) #绘图 need CBA bag Require (CBA, quietly=true) #method曼哈顿距离, Ward Deviation squared and Chcluster <-hclusterpar (Na.omit (Data[,c (1:2)]), method= " Manhattan ", link=" Ward ", nbproc=2) Chcluster # Cluster Center Centers.hclust (Na.omit (Data[,c (1:2)]), Chcluster, 3) #产生树形图 rectangular display of cluster junctions Fruit par (bg= "grey") plot (Chcluster, main= "", sub= "", xlab= "", Labels=false, hang=0) rect.hclust (Chcluster, k=3) #加标题 title (m Ain= "Hcluster_dendrogram_data", Sub=paste ("R", Format (Sys.time (), "%y-%b-%d%h:%m:%s"), Sys.info () ["User"]) # Correlation between classes and classes par (bg= "yellow") Plotcluster (Na.omit (Data[,c (1:2)]), Cutree (Chcluster, 3)) title (main= "discriminant Coordinates data ", Sub=paste (" R ", Format (Sys.time (),"%y-%b-%d%h:%m:%s "),Sys.info () ["User"]) #数据集的聚类效果图 plot (Data[,c (1:2)], Col=cutree (Chcluster, 3)) title (main= "", Sub=paste ("R", Format ( Sys.time (), "%y-%b-%d%h:%m:%s"), Sys.info () ["User"]) #验证聚类结果的基本统计信息 cluster.stats (Dist (Na.omit (1:2))), Cutree (Chcluster, 3)) #输出结果 Result<-cbind (Data,cutree (chcluster,3)) write.csv (result, "cengciresult.csv")