I've looked through the API documentation but there doesn't seem to be
much info on parameter selection using the RBF kernel in a SVM
classifier. The literature suggests various heuristic or brute-force
approaches for determining Gamma and C, though it's not clear to me if
this happens during classifier training:
clf = RbfCSVMC()
cv = CrossValidatedTransferError(TransferError(clf),
NFoldSplitter(cvtype=n), enable_states=['confusion', 'samples_error'])
cv(dataset)
When I run this code using default values of gamma or C, it generates
a result, but shouldn't this parameter selection be part of classifier
training?
thanks,
Eric
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