# Matlab Bayesian Network toolbox and continuous values

I have two doubt, one about theory and one about practical problem.

First i have not full understand how to work a bayesian network with continuous values. I have learn that i can approximate P(A) (the probability of node A) with a Gaussian Distribution. But i have a dataset, mean and variance of the Gaussian Distribution is the mean and the variance of the dataset ?

And if i have P(A|B,C), with A and B with continuous values, how i can represent with a Gaussian Distribution?

The practical problem is i need to learn a a Bayesian Structure from a continuous values Dataset and i use this toolbox for matlab: http://code.google.com/p/bnt/ (Bayes Net Toolbox for Matlab by Kevin Murphy)

Now how i can use to learn a Bayesian Structure from a Dataset (of continuous values) with this tools?

If i use learn_struct_K2 function i need the order of nodes but where i can get this order? There are other useful functions in this toolbox that you know? (About this problem)

• I have a similar problem, did you find a way to do it? I would appreciate some advice. Cheers. – user45208 May 8 '14 at 14:26
• @Neptune, General answer to this is: toolboxes and modules for structure learning, parameter learning, and inference for BN's with continuous nodes is a very under-developed topic. The vast majority of BN applications discretise their continuous values. – Zhubarb May 8 '14 at 15:00
• and I'm go to discretise too. – Neptune Jul 4 '14 at 19:50