| Library: | xclust |
| See also: | xchcme |
| Quantlet: | xcfcme | |
| Description: | Performs a fuzzy c-means cluster analysis |
| 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 | |
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)
gives the partitions of membership functions and depicts the clusters based on these partitions