Hello, I need help with this. Let's say that I have n features that I want to use to predict which class an observation belongs to. Using training data I try to do the following:
> training$result <- as.factor(training$result) > model <- glm(result ~., family=binomial("logit"), data = training) However, when I run the model on my test data I receive predictions that have continuous values. I.e. if I have the classes 0 and 1 in "results" I get predictions of 0.234235 and so on. How do I force the output to be just 0 or 1? What am I missing? Thanks! John -- View this message in context: http://old.nabble.com/GLM%3A-Classification-problem.-Help%21-tp26416707p26416707.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.