Hi useR's,
I am resending this request since I got no response for my last post and I
am new to the list so pardon me if I am violating the protocol.
I am trying to use the "Kernlab" package for training and prediction using
SVM's. I am getting the following error when I am trying to use the predict
function:
> predictSvm = predict(modelforSVM, testSeq);
Error in `contrasts<-`(`*tmp*`, value = "contr.treatment") : contrasts can
be applied only to factors with 2 or more levels
The training file is a data frame with 501 columns: Col 1 is "Class" which
is "+" or "-" and Cols V1 to V500 are "A/C/G/T" . There are 200 seq's for
training (100 + and - each). this is very similar to the "promotergene" data
set included as example with the package.
The model that I have generated is as follows:
modelforSVM <- ksvm(Class ~ ., data = train500, kernel = "rbfdot", kpar =
"automatic", C = 60, cross = 3, prob.model = TRUE)
The testSeq is a vector of 500 characters casted as a data.frame. I tried
adding the Class column as well later to the testSeq data frame but got the
same error.
I am using R with windows, 32 bit, version 2.9.0
Any help that I can get is really appreciated.
Thanks,
Vishal
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