Nothing
library(Thresher)
# get saved data
data(savedSims)
reap <- savedReap[[5]]
dset <- reap@data
labels <- factor(paste("C", predict(reap@fit), sep=""))
# use a different clustering algorithm
hc <- hclust(distanceMatrix(dset, "uncentered"), "average")
newLabels <- paste("New", cutree(hc, k=3), sep="")
tab <- table(OLD=labels, NEW=newLabels)
tab
# now test the methods
indices <- labelMatcher(tab)
tab[indices$ii, indices$jj]
matchLabels(tab)
countAgreement(tab)
labelAccuracy(dset, labels)
bestMetric(dset, labels)
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