PE {fclust} | R Documentation |
Partition entropy
Description
Produces the partition entropy index. The optimal number of clusters k is is such that the index takes the minimum value.
Usage
PE (U, b)
Arguments
U |
Membership degree matrix |
b |
Logarithmic base (default: exp(1)) |
Value
pe |
Value of the partition entropy index |
Author(s)
Paolo Giordani, Maria Brigida Ferraro, Alessio Serafini
References
Bezdek J.C., 1981. Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York.
See Also
PC
, MPC
, SIL
, SIL.F
, XB
, Fclust
, Mc
Examples
## McDonald's data
data(Mc)
names(Mc)
## data normalization by dividing the nutrition facts by the Serving Size (column 1)
for (j in 2:(ncol(Mc)-1))
Mc[,j]=Mc[,j]/Mc[,1]
## removing the column Serving Size
Mc=Mc[,-1]
## fuzzy k-means
## (excluded the factor column Type (last column))
clust=FKM(Mc[,1:(ncol(Mc)-1)],k=6,m=1.5,stand=1)
## partition entropy index
pe=PE(clust$U)
[Package fclust version 2.1.1.1 Index]