## create kernel object for normalized spectrum kernel
specK5 <- spectrumKernel(k=5)
## Not run:
# ## load data
# data(TFBS)
#
# ## perform training - feature weights are computed by default
# model <- kbsvm(enhancerFB, yFB, specK5, pkg="LiblineaR",
# svm="C-svc", cost=15, cross=10, showProgress=TRUE)
# showProgress=TRUE)
#
# ## show result of validation
# cvResult(model)
# ## show feature weights
# featureWeights(model)[1:5]
# ## show model offset
# modelOffset(model)
# ## End(Not run)
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