mestimate: Estimate for optimal fuzzifier m

Description Usage Arguments Details Value Author(s) References Examples

Description

This function estimates an optimal setting of fuzzifier m

Usage

1
mestimate(eset)

Arguments

eset

object of class “ExpressionSet”

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.

Value

Estimate for optimal fuzzifier.

Author(s)

Matthias E. Futschik (http://itb.biologie.hu-berlin.de/~futschik)

References

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

Examples

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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))
}


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