On Wed, 11 Jul 2007 [EMAIL PROTECTED] wrote: > The problem is, that the functions > result=classifier(formula, data, subset, na.action, control = > Weka_control(mycontrol)) > do not seem to be manipulated by the mycontrol- arguments
Yes, they are...not all parameter changes have always an effect on the specified learner. > Perhaps this should be resepected via the handlers- argument , > but the documentation in this regard is rather sparse. Handlers are not needed here. Re: sparse docs. In case you have not seen that paper already, there is a technical report on the ideas behind RWeka: http://epub.wu-wien.ac.at/dyn/openURL?id=oai:epub.wu-wien.ac.at:epub-wu-01_ba6 Re: SMO. Compare m1 <- SMO(Species ~ ., data = iris) m2 <- SMO(Species ~ ., data = iris, control = Weka_control( K = "weka.classifiers.functions.supportVector.RBFKernel")) which yield different results so the Weka_control() works. The same happens if you register the mySMO() interface yourself. I'm not sure why the "E = ..." argument has no influence on the SMO, please check the Weka docs for this particular learner. Best, Z ______________________________________________ R-help@stat.math.ethz.ch 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.
