## Not run:
# require(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")
# pl <- plGrid(array.train, array.valid = arrays[[2]], how = "buildSVM",
# kernel = c("linear", "radial"), cost = 10^(-3:3), gamma = 10^(-3:3))
# ## End(Not run)
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