Short answer, if you’re only interested in solving a prediction task: use Naive Bayes. A Bayesian network (has a good wikipedia page) models relationships between features in a very general way. If you know what these relationships are, or have enough data to derive them, then it may be appropriate to use a Bayesian network. … Read more
I’ve been working on this kind of thing in my spare time for quite a while. I think I’m on my third or fourth version of this same problem right now. I’m actually getting ready to release another version of Fathom (https://github.com/davidrichards/fathom/wiki) with dynamic bayesian models included and a different persistence layer. As I’ve tried … Read more
Decision Trees are very flexible, easy to understand, and easy to debug. They will work with classification problems and regression problems. So if you are trying to predict a categorical value like (red, green, up, down) or if you are trying to predict a continuous value like 2.9, 3.4 etc Decision Trees will handle both … Read more