Hello all,
I am using the e1071 SVM with the tune options for classification, which work
pretty well, given the examples of using tune.svm function for classification.
But I have not found any example to tune the SVM novelty detection
(one-classification) parameters (gamma, cost, nu), for example this are some of
the options I have tried with no success:
obj<-tune(svm, x,y, type ="one-classification", gamma=2^(-1:1), cost=2^(1:3),
nu=2^(-3:-1))
obj<-tune(svm, x,y, type ="one-classification", cost=2^(1:3), nu=2^(-3:-1))
obj<-tune(svm, x,y, type ="one-classification", gamma=2^(-1:1), nu=2^(-3:-1))
obj<-tune(svm, x,y, type ="one-classification", nu=2^(-3:-1))
obj<-tune(svm, x,y, type ="one-classification", gamma=2^(-1:1), cost=2^(1:3))
y is expressed as factor of [ 1,-1] values
also I tried:
obj<-tune(svm, x,y, type ="one-classification", ranges = list(gamma=2^(-1:1),
cost=2^(1:3), nu=2^(-3:-1)))
and all the parameters combination showed above, but always the same message:
Error in tune(svm, x, y, ranges = ......, type = "one-classification") :
Dependent variable has wrong type!
But if I try:
svm.model <-svm(x,y,type = "one-classification",gamma=2, cost =3, nu=0.001)
it runs without problems. Please, let me know whether what I should change in
my code or the e1071 tune function does not work with SVM one-classification
Alfonso Torres
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