On Nov 18, 2009, at 5:12 PM, J_Laberga wrote:
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?
The fact that predict gives you probabilities? If you want a decision,
then you need to specify a decision rule, i.e. a threshold.
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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