So, I want to estimate the probability that a student will succeed or fail in a particular major (suppose success means in this case to graduate with that major) based on data from that student's application. I have a lot of records of past students' application data and success.
I am aware that I could try logistic regression, but I would like to know all my options, including methods which allow more easily for non-linearities.
If I were just trying to classify incoming students, I think I would try an SVM model. But I don't know how easy it is to adapt that method to the task of estimating probabilities.
Much of the data is categorical. Often binary. Some features are real numbers / integers, as well.