Bayesian network learning with cutting planes

Details Bayesian network learning with cutting planes Bayesian network learning with cutting planes

2012-02-14

arxiv.org/abs/1202.3713v1

Computer Science

Artificial Intelligence

Scientific paper

The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisation problem where the goal is to find a BN structure which maximises log marginal likelihood (BDe score). Integer programming, specifically the SCIP framework, is used to solve this optimisation problem. Acyclicity constraints are added to the integer program (IP) during solving in the form of cutting planes. Finding good cutting planes is the key to the success of the approach -the search for such cutting planes is effected using a sub-IP. Results show that this is a particularly fast method for exact BN learning.

Affiliated with

Also associated with

No associations

Rating

Bayesian network learning with cutting planes does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Bayesian network learning with cutting planes, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Bayesian network learning with cutting planes will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-90403