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Datamining r 5th

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Datamining r 5th

  1. 1. R: (1)K-meanssesejun@is.ocha.ac.jp 2010/12/09
  2. 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. 3. 51. k-menas kmeans_sample_a.tab kmeans_sample_b.tab2. k-means 1 k3.4. 2 15. k-means usps_cluster_large.tab k k 5 • usps_cluster_large.tab 0 9 5 50• 1 6 15:00 ( )
  4. 4. kmeans_sample_a.tab
  5. 5. kmeans_sample_b.tab

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