training svm
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
<soumyadeep_nandi at yahoo.com> 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
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