fclust: PE – R documentation

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PE

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.

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)

fclust

Fuzzy Clustering

v2.1.1

GPL (>= 2)

Authors

Paolo Giordani, Maria Brigida Ferraro, Alessio Serafini

Initial release

2019-09-16

PE