Stephen:
Your calls to best.svm() do not tune anything unless you specify the
parameter ranges (see the examples on the help page). Your calls are
just using the defaults which are very unlikely to yield models with
good performance.
[I think some day, I will have to remove the defaults in
Hi
I am doing this sort of thing:
POLY:
obj = best.tune(svm, similarity ~., data = training, kernel =
polynomial)
summary(obj)
Call:
best.tune(svm, similarity ~ ., data = training, kernel = polynomial)
Parameters:
SVM-Type: eps-regression
SVM-Kernel: polynomial
