I'm trying to learn the principles of artificial intelligence. I just finished coding up a belief net and a corresponding EM algorithm that learns the CPTs for latent nodes using training data (if you're unfamiliar with the lingo, you're probably going :eek: right now). While the program (written in Python, of course) works and is pretty quick, it is also pretty unstructured - I had difficulty figuring out how to best represent probability computations, so parts of the algorithm look kind of awkward.
Are there any good, complete AI/machine learning packages in Python - are there any which incorporate Bayesian belief nets? Any which represent the belief net, the update procedure, and EM algorithms to find the parameters at latent nodes? How about BioPython? Since I'm a computational biology guy, that would be right up my alley, but I'm not sure how complete the BioPython package is. How about Orange - how easily does it lend itself to bioinformatics-type applications? Does anyone here have any experience with this stuff? If not, I guess I'll start plumbing it myself, but I'd appreciate it if anyone could save me some time :cheesy:.
Here's a link to BioPython's homepage, if anyone is interested in learning:
And here is Orange: