Nothing
EvalClrule <- function(darule,VData,Vgrp,k)
{
grpcodes <- levels(Vgrp)
errates <- array(dim=k)
Nk <- array(dim=k)
clres <- predict(darule,VData)$class
if (k>2) Cmat <- matrix(nrow=k,ncol=k,dimnames=list(grpcodes,grpcodes))
else Cmat <- NULL
for (grpInd in 1:k)
{
# Nk[grpInd] <- length(Vgrp[Vgrp==grpcodes[grpInd]])
Nk[grpInd] <- length(which(Vgrp==grpcodes[grpInd]))
thisgrpclres <- clres[Vgrp==grpcodes[grpInd]]
levels(thisgrpclres) <- grpcodes
thisgrperr <- thisgrpclres[grpcodes[grpInd]!=thisgrpclres]
if (Nk[grpInd]>0) {
errates[grpInd] <- length(thisgrperr)/Nk[grpInd]
} else {
errates[grpInd] <- 0
}
for (grpInd2 in 1:k) Cmat[grpInd,grpInd2] <- length(which(thisgrpclres==grpcodes[grpInd2]))
}
list(err=errates,Nk=Nk,Cmat=Cmat) # return(list(err=errates,Nk=Nk,Cmat=Cmat))
}
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