Well, I know there must be something wrong with the way I'm running the SVM but I tried all the posiible ranges of parameters gamma and cost and it does not improve? Could You suggest anything?
On Wed, 1 Feb 2006, Uwe Ligges wrote: > Georges Orlowski wrote: > > > I'm running SVM from e1071 package on a data with ~150 columns (variables) > > and 50000 lines of data (it takes a bit of time) for radial kernel for > > different gamma and cost values. > > > > I get a very large models with at least > > 30000 vectors and the prediction I get is not the best one. What does it > > mean and what could I do to ameliorate my model ? > > Do you mean 30000 *support vectors* in 50000 observations? So you are > heavily overfitting. Try to tune the svm better.> > Uwe Ligges > > > > > > Jerzy Orlowski > > > > ______________________________________________ > > [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 > ______________________________________________ [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
