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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 ( )
4.
5.
kmeans_sample_a.tab
6.
kmeans_sample_b.tab
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