[R] handling constant factors in prediction using svm

[Uwe Ligges]

On 04.10.2011 08:53, Divyam wrote:
> Hi users!
>
> I am fitting a model with several factor variables as independents using
> svm. since there are lots of categorical variables,the training and test
> data sets have been created using dummy.data.frame option from dummies
> package. I have a factor A in the training data set with 2 levels (0,1).In
> the test set, this factor A has only 1 level (1) and hence when applying
> dummy.data.frame, the variable gets dropped(and that's how i want it too).
> The problem comes when I am trying to predict the test data as an error is
> thrown saying A0 object is not found. Is there anyway  to solve this
> problem?

Errr, if you learned a model that predicts based on several variables, 
including A0, what do you expect what happens if A0 is not given? Well, 
you cannot predict. So if A0 is constant in your test cases, just supply it!

To simplify, consider a linear model y=bX+e. Now one column of X is 
missing for prediction. y will be undefined, obviously.

Uwe Ligges





> Thanks
> Divya
>
> --
> View this message in context: http://r.789695.n4.nabble.com/handling-constant-factors-in-prediction-using-svm-tp3870093p3870093.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at 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.