Re: [R] GLM: What is a good way for dealing with new factor levels in the test set?

For anyone who is looking for an answer to this in the future... I went for "imputation". It's a way of filling in missing variables based off of what you see elsewhere in the data. Myself, I simply took a sample of the categorical from the rest of the test set. Some may argue that this is erro

Re: [R] GLM: What is a good way for dealing with new factor levels in the test set?

Hi, Thanks for the reply! I did try this... # res is a data frame levels(res$mytypeid.f) <- c(levels(res$mytypeid.f),"mynewlevel") logreg <- glm(yesno ~ mytypeid.f + amount, data=res, family="binomial") exp(coef(logreg)) # this result shows that the new level is not included in the regression.

[R] GLM: What is a good way for dealing with new factor levels in the test set?

My training set and my test set have some factor levels that are different It's rare, but it occurs. What is a good way for dealing with this? I don't want to throw away the entire row from the data frame, because there is some valuable information in there. Is there some way to say somethi