Description Usage Arguments Details Value Author(s) References Examples
This function estimates an optimal setting of fuzzifier m
1 | mestimate(eset)
|
eset |
object of class “ExpressionSet” |
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.
Estimate for optimal fuzzifier.
Matthias E. Futschik (http://itb.biologie.hu-berlin.de/~futschik)
Schwaemmle and Jensen, Bioinformatics,Vol. 26 (22), 2841-2848, 2010
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | 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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Attaching package: 'BiocGenerics'
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clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
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IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, basename, cbind, colMeans, colSums, colnames,
dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
intersect, is.unsorted, lapply, lengths, mapply, match, mget,
order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
union, unique, unsplit, which, which.max, which.min
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