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@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.
______________________________________________ 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.
