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: xchcme

Macro: xcfcme
Description: Performs a fuzzy c-means cluster analysis

Reference(s):

Usage: {v,d,uu,clus}=xcfcme(x,c,m,e,alpha)
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
alpha level of the fuzzy set [0,1]
Output:
v p x p matrix of cluster centers
d n x p matrix of distance
uu n x p matrix of result

Example:

library("xclust")
z=read("butterfly.dat")
x=z[,2:3]
c=2
m=1.25
e=0.001
alpha=0.9     
fcm=xcfcme(x,c,m,e,alpha)     ; apply fuzzy-c-means clustering
fcm.clus
d=createdisplay(1,1) 
setmaskp(x,fcm.clus,fcm.clus+3,8)
show(d,1,1,x)
title="Fuzzy-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: xchcme

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, 17.8.2000