Mfuzz (version 2.32.0)

mestimate: Estimate for optimal fuzzifier m

Description

This function estimates an optimal setting of fuzzifier m

Usage

mestimate(eset)

Arguments

eset

object of class “ExpressionSet”

Value

Details

Schwaemmle and Jensen proposed an method to estimate of m, which was motivated by the evaluation of fuzzy clustering applied to randomized datasets. The estimated m should give the minimum fuzzifier value which prevents clustering of randomized data.

References

Schwaemmle and Jensen, Bioinformatics,Vol. 26 (22), 2841-2848, 2010

Examples

if (interactive()){
data(yeast)
# Data pre-processing
yeastF <- filter.NA(yeast)
yeastF <- fill.NA(yeastF)
yeastF <- standardise(yeastF)

#### parameter selection

#### parameter selection
# For fuzzifier m, we could use mestimate
m1 <- mestimate(yeastF)
m1 # 1.15

cl <- mfuzz(yeastF,c=20,m=m1)
mfuzz.plot(yeastF,cl=cl,mfrow=c(4,5))
}