1. R:
(1)
K-means
sesejun@is.ocha.ac.jp
2010/12/09

2. k-means
> usps<-read.table("usps/usps_cluster.csv", header=T, sep=",")
> usps.sub<-usps[3:length(usps)]
> rownames(usps.sub)<-usps$ImageName
> usps.kmeans<-kmeans(usps.sub, 3, iter.max=100)
> usps.kmeans$size
[1] 5 2 3
> usps.kmeans$cluster
[1] 2 3 3 1 1 2 3 1 1 1
> usps.kmeans

3. 5
1. k-menas kmeans_sample_a.tab
kmeans_sample_b.tab
2. k-means
1
k
3.
4. 2 1
5. k-means usps_cluster_large.tab k
k 5
• usps_cluster_large.tab 0 9 5 50
• 1 6 15:00 ( )

5. kmeans_sample_a.tab

6. kmeans_sample_b.tab