Noah Silverman wrote:> Hi,
>
> I have a process using svm from the e1071 library.
It's called a *package* which is probably installed in a *library* of
packages.
> it works.
>
> I want to try using the KSVM library instead. The same data used wiht
> e1071 gives me an error with KSVM.
I guess you are talking about the ksvm *function* in *package* kernlab
now, right?
>
> My data is a data.frame.
>
> sample code:
>
> svm_formula <- formula(y ~ a + B + C)
You do not use svm_function below, do you?
> svm_model <- ksvm(formula, data=train_data, type="C-svc",
> kernel="rbfdot", C=1)
>> I get the following error:
>
> "object is not a matrix"
ksvm works for me. Please specify a reproducible example (including the
data) or give us at least the output of str(data) and specofy which
verions of R and kernlab you are talking about.
Uwe Ligges
> So I tried this:
>
> svm_model <- ksvm(formula, data=as.matrix(train_data),
type="C-svc",
> kernel="rbfdot", C=1, scaled=FALSE)
>
> Now I get this error:
> "Error in model.fram.definition(data = list(v1 = c(1.1234, -2.3232:
> Object is not a matrix
>
> My data was previously scaled with the scale() function so that the mean
> is centered at 0. and the range is {-1,1}
>
> Can anyone provide some suggestions as to why I'm getting an error?
>
> Thanks!
>
> -N
>
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