[R] r kernlab find best cost parameter automatically
m@rong|u@|u|g| @end|ng |rom gm@||@com
Thu May 23 09:19:34 CEST 2019
I am using kernlab to implement an SVM analysis. The model I am
building has the syntax:
`ksvm(<y> ~ <x>, data = <dataframe>, type = "C-svc", kernel =
"rbfdot", kpar = "automatic", C = <k>, prob.model = TRUE)`
Here, I can use different values of `k` to give different costs to the
model. Each time I give a different k, the results obviously change.
Would be possible to automate the selection of the best <k> value?
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