Quantum Bayesian Networks

August 27, 2008

Bayesian Networks

Filed under: Uncategorized — rrtucci @ 1:11 am

A Bayesian network consists of a DAG (directed acyclic graph, i.e. a network) together with a conditional probability matrix assigned to each node of the net. One can represent any probability distribution P(x1,x2….) as a Bayesian net, where each variable x1,x2… corresponds to a different node of the graph. Bayesian nets are used to pose and solve inference problems graphically. Bayesian nets generalize Bayes rule, which corresponds to the case of a two node net. A fun way to start learning about Bayesian nets is to download one of the many free or trial-version software applications that implement Bayesian nets, and to go through its tutorial. At the end of this article, you will find a list of such software. Enjoy!


Leave a Comment »

No comments yet.

RSS feed for comments on this post. TrackBack URI

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )


Connecting to %s

Create a free website or blog at WordPress.com.

%d bloggers like this: