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