# NOT RUN {
library(golubEsets)
data(Golub_Merge)
array <- arrayEset(Golub_Merge, colBy = "ALL.AML", include = list("ALL", "AML"))
array <- modFilter(array, 20, 16000, 500, 5) # pre-filter Golub ala Deb 2003
array <- modTransform(array) # lg transform
array <- modNormalize(array, c(1, 2)) # normalize gene and subject vectors
arrays <- splitSample(array, percent.include = 67)
array.train <- fsStats(arrays[[1]], top = 0, how = "t.test")
array.train <- fsPrcomp(array.train, top = 50)
mach <- buildSVM(array.train, top = 5, kernel = "linear", cost = 1)
# }
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