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> I am trying to tune an svm by doing the following: > > tune(svm, similarity ~., data = training, degree = 2^(1:2), gamma = > 2^(-1:1), coef0 = 2^(-1:1), cost = 2^(2:4), type = "polynomial") I think you want to set `kernel' not `type'... > but I am getting > > Error in svm.default(x, y, scale = scale, ...) : > wrong type specification! ...checking the argument `type' on ?svm would have told you that. > I have to admit I am not sure what I am doing wrong. Could anyone > tell me why the parameters I am using are wrong? > > Plus could anyone tell me how to go about picking the correct ranges > for my tuning? Surprisingly, you have to set `ranges' to specify the ranges of the parameters, e.g., obj <- tune(svm, Species ~ ., data = iris, ranges = list(degree =2^(1:2), gamma = 2^(-1:1), coef0 = 2^(-1:1), cost = 2^(2:4)), kernel = "polynomial") I'm not sure what good ranges are to tune an SVM with a polynomial kernel... hth, Z ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html