My predictions coming from a logistic regression model (glm in R) are not bounded between 0 and 1 like I would expected. My understanding of logistic regression is that your input and model parameters are combined linearly and the response is transformed into a probability using the logit link function. Since the logit function is bounded between 0 and 1, I expected my predictions to be bounded between 0 and 1.
However that's not what I see when I implement logistic regression in R:
data(iris) iris.sub <- subset(iris, Species%in%c("versicolor","virginica")) model <- glm(Species ~ Sepal.Length + Sepal.Width, data = iris.sub, family = binomial(link = "logit")) hist(predict(model))
If anything the output of predict(model) looks normal to me. Can anyone explain to me why the values I get are not probabilities?