A rather technical workaround I see could be adding a row with a different value. But if a column only ever has one value, then it contributes nothing to the model and I see no reason why it would have to be kept. ~ Oldrich Kruza
On Fri, Mar 7, 2008 at 6:45 AM, Soumyadeep nandi <[EMAIL PROTECTED]> wrote: > What should I do if I need to train svm() with data having same value across > all rows in some columns. These must be the important features of the class > and we cant exclude these columns to build up models. > > The error I am getting is: > Error in predict.svm(ret, xhold) : Model is empty! > In addition: Warning message: > In svm.default(datatrain, classtrain) : > Variable(s) 'F112' and 'F113'.... [... truncated] > > Is there any way to overcome this problem? Any suggestions would be highly > helpful. > > Regards > Soumyadeep > > > ________________________________ > Be a better friend, newshound, and know-it-all with Yahoo! Mobile. Try it > now. ______________________________________________ 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.
