Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library: xclust
See also: xcfcme

Quantlet: xchcme
Description: Performs a hard c-means cluster analysis

Reference(s):

Usage: {v,d,uu,clus}=xchcme(x,c,m,e)
Input:
x n x p matrix of n row points to be clustered
c scalar the number of clusters
m determines the fuzziness of clustering (m>1)
e termination tolerance
Output:
v p x p matrix of cluster centers
d n x p matrix of distance
uu n x p matrix of result
clus number of cluster

Example:



library("xclust")

z=read("butterfly.dat")

x=z[,2:3]

c=2

m=1

e=0.001

hcm=xchcme(x,c,m,e)         ; apply hard-c-means clustering

hcm.clus

d=createdisplay(1,1)

setmaskp(x,hcm.clus,hcm.clus+1,7)

show(d,1,1,x)

title="Hard-c-means for Butterfly Data"

setgopt(d,1,1,"title", title)  

Result:

gives the partitions of membership functions and depicts 

the clusters based on these partitions


Library: xclust
See also: xcfcme

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Author: Hans-Joachim Mucha, Hizir Sofyan, 000510
(C) MD*TECH Method and Data Technologies, 21.9.2000