Maximum Likelihood parameters + categorical attributes + Gibbs sampling (Migrated from community.research.microsoft.com) RRS feed

  • Question

  • Kirali posted on 01-30-2011 3:19 PM


    I am new to infer.net, I am wondering if infer.net is the best tool to solve my needs. I have a bayesian network with 10 nodes. Each node has categorical values, with number of values ranging from 25 to 500. I am currently using Kevin Murphy's BNT to learn the Maximum Likelihood parameters (for the conditional probability tables). I am currently doing Gibbs sampling in BNT. But it is too slow for my purpose. I am wondering if infer.net can be used for this purpose?

    Thanks for your time in advance.





    Friday, June 3, 2011 6:17 PM