Hi,
according to ?rvm the relevance vector machine function as implemented in the
kernlab-package
has an argument 'cross' with which you can perform k-fold cross validation.
However, when I try to add a 10-fold cross validation I get the following error
message:
Error in match.arg(type, c("C-svc", "nu-svc", "kbb-svc", "spoc-svc", "C-bsvc",
:
'arg' should be one of “C-svc”, “nu-svc”, “kbb-svc”, “spoc-svc”, “C-bsvc”,
“one-svc”, “eps-svr”, “eps-bsvr”, “nu-svr”
code-example:
# create data
x <- seq(-20,20,0.1)
y <- sin(x)/x + rnorm(401,sd=0.05)
# train relevance vector machine
foo <- rvm(x, y, cross=10)
So, does that mean that cross-validation is not working for rvm at the moment?
(since the type argument only allows support vector regression or
classification)
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