Hello, Alexandre, In R you can specify whether to use or not scaling with parameter scale, e.g.: model<-svm(class_var ~ ., data=trainset, scale=FALSE);
Don't forget to disable it if you already sclaed your data with libsvm svm-scale algorithm. Best, -Alex ________________________________________ From: r-help-boun...@r-project.org [r-help-boun...@r-project.org] on behalf of Alexandre Marié [alexandre.ma...@artelys.com] Sent: 29 March 2012 13:22 To: r-help@r-project.org Subject: [R] TR: [e1071] Load an SVM model exported with write.svm Dear R help mailing list, I work on a project using the SVM implementation from e1071 R package and I really need your help in order to use correctly the write.svm function. I trained my SVM model in R and I would like to use this model in Java. To do that, I would like to use the libsvm Java version (I tried to used jlibsvm, in order to benefit from the refactoring, but it does not seem to work and the lack of documentation push me to switch to the libsvm java version). Thus, I exported my model with the function write.svm and import it with the libsvm java library but I didn’t obtain the expected result from my test data set. I suspect that the load of the model file is not enough and it is necessary to use the .scale file, in Java, to scale the data (I suspect that the model object in R contains the scaling) but I don’t know how to do that. In order to understand how it is working, I would like, in the first place, load the file generated by write.svm in R in order to be sure the model in the file match with my R object. But I don’t find any function to load that kind of file. How could I load a model file generated by write.svm in R? Thanks a lot in advance for your help! Best regards, _____ Alexandre Mariι Artelys : www.artelys.com [[alternative HTML version deleted]] ______________________________________________ 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.