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

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

  Hi,

  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.

  Kirali

   

   

   

  Friday, June 3, 2011 6:17 PM