最近在学聚类分析 在网上发现一个用R写的聚类算法 但是自己怎么也调不通 求大牛帮个忙

Question

结果显示迭代没问题，但是簇间距离是0那应该就是把所有的数据都算作一类了
My_kmeans<-function(data,k,max.iter=10){

rows<-nrow(data)
cols<-ncol(data)

within<-matrix(0,nrow=k,ncol=1)
between<-0
iter=0

indexMatrix<-matrix(0,nrow=rows,ncol=2)

centers<-matrix(0,nrow=k,ncol=cols)
randSeveralInteger<-as.vector(sample(1:rows,size=k))
for(i in 1:k){
indexMatrix[randSeveralInteger[i],1]<-i
centers[i,]<-data[randSeveralInteger[i],]
centers<-matrix(centers,k,cols)
}
changed=TRUE #changed

while(changed){

if(iter>=max.iter)
  break

changed=FALSE


for(i in 1:rows){ 
  initialDistance<-10000 
  previousCluster<-indexMatrix[i,1]
  for(j in 1:k){ 
    currentDistance<-(sum((data[i,]-centers[j,])^2))^0.5
    if(currentDistance<=initialDistance)
       initialDistance<-currentDistance 
       indexMatrix[i,1]<-j 
       indexMatrix[i,2]<-currentDistance  
  } 
}


if(previousCluster!=indexMatrix[i,1]) 
  changed=TRUE

}

for(m in 1:k){
clusterMatrix<-data[indexMatrix[,1]==m,]
clusterMatrix<-as.matrix(clusterMatrix)
if(nrow(clusterMatrix)>0){
centers[m,]<-colMeans(clusterMatrix)
}
else{
centers[m,]<-centers[m,]
}

iter=(iter+1)
}

ss<-function(x) sum(scale(x,scale=FALSE)^2)
between<-ss(centers[indexMatrix[,1],])
within<-sapply(split(as.data.frame(data),indexMatrix[,1]),ss)
twithin<-sum(within) #total within-clustersum of squares

result<-list(cluster=indexMatrix[,1],tot.withinss=twithin,betweenss=between,iteration=iter)

return(result)
}