# train classifier on Alon's Colon Cancer Data Set
#(after a logarithmic transformation).
log10genes <- log10(AlonDS[,-1])
ldarule <- Dlda(log10genes,AlonDS$grouping)
# show classification rule
print(ldarule)
# get in-sample classification results
predict(ldarule,log10genes,grpcodes=levels(AlonDS$grouping))$class
# compare classifications with true assignments
cat("Original classes:\n")
print(AlonDS$grouping)
# Estimate error rates by four-fold cross-validation.
# Note: In cross-validation analysis it is recommended to set
# the argument 'ldafun' to "classification", in order to speed up
# computations by avoiding unecessary eigen-decompositions
if (FALSE) {
CrosValRes <- DACrossVal(log10genes,AlonDS$grouping,TrainAlg=Dlda,
ldafun="classification",kfold=4,CVrep=1)
summary(CrosValRes[,,"Clerr"])
}
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