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