Hello, together
I'm trying to use user defined kernel. I know that kernlab offer user
defined kernel(custom kernel functions) in R.
I used data spam including package kernlab.
(number of variables=58 number of examples =4061)
i'm user defined kernel's form,
kp=function(d,e){
as=v*d
bs=v*e
cs=as-bs
cs=as.matrix(cs)
exp(-(norm(cs,"F")^2)/2)
}
class(kp)="kernel"
It is the transformed kernel for gaussian kernel.
v is the continuously changed values that are inverse of standard deviation
vector about each variables.
(ex: v=(0.1666667,........0.1666667)`, length(v)= 57)
training set defined 60% of spam data.
(preserving the proportions of the different classes.)
if data's type is spam, than data`s type = 1 for train svm (else -1)
m=ksvm(xtrain,ytrain,type="C-svc",kernel=kp,C=10)
But, this step is not working. always Waiting for a response.
So, I ask you this problem, why?
number of examples are too big?
Is there any other R package that can train SVMs for user defined kernel?
I want to your answer.
Thanks in advance!
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