I have a trained SVM that I want to export with write.svm and eventually use in libSVM. Some of my features are factors. Standard libSVM only works with features that are doubles, so I need to figure out how my features should be represented and used.
How does e1071 treat factors in an SVM? For feature "foo" with values "a" and "b" I'm assuming it's something like foo_a (0 or 1) and foo_b (0 or 1). Is that right? Do factors get treated differently in an SVM? If I convert the factors to intergers for libSVM, I'll lose the information that a feature doesn't take on a range of values. Is that going to cause problems? I don't know if the model takes that into account. When using write.svm a scale file is also output. My scale file is missing the same number of rows as I have features that are factors. That's another indication to me that the factors are causing issues. Thanks. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.