proc()=main(x,x46)
; compute the euclidean distance between banknotes
i=0
d=0.*matrix(rows(x),rows(x))
while (i.<cols(x))
i = i+1
d = d+(x[,i] - x[,i]')^2
endo
d = sqrt(d)
; use the WARD method to cluster the data
t = agglom (d, "WARD", 3)
d=createdisplay(2,1)
setmaskp(x46,t.p,t.p+1,7)
show(d,1,1,x46)
title="Ward Method for Bank Notes Data with three clusters"
setgopt(d,1,1,"title", title)
endp
;
library("xclust")
x=read("bank2.dat")
x4=x[,4]
x6=x[,6]
x46=x4~x6
main(x,x46) ; apply ward method
c=3 ; initialize for fuzzy c-means clustering
m=1.25
e=0.001
alpha=0.5
fcm=xcfcme(x,c,m,e,alpha) ; apply fuzzy-c-means clustering
setmaskp(x46,fcm.clus,fcm.clus+1,7)
show(d,2,1,x46)
title="Fuzzy-c-means for Bank Notes Data with three clusters"
setgopt(d,2,1,"title", title)