Cornell University
Library
Cornell UniversityLibrary

eCommons

Help
Log In(current)
  1. Home
  2. Cornell University Graduate School
  3. Cornell Theses and Dissertations
  4. Results in Computational Algebra of Bayesian Networks

Results in Computational Algebra of Bayesian Networks

File(s)
compalgbns.pdf (1.69 MB)
Permanent Link(s)
https://hdl.handle.net/1813/3364
Collections
Cornell Theses and Dissertations
Author
Sinnott, Steven
Abstract

This dissertation studies the algebraic varieties arising from the conditional independence statements of Bayesian networks. Reduction techniques are described for relating these varieties to the varieties for smaller Bayesian networks. Particular attention is paid to the issues of primality, dimension, and degree. A classification of 5-node Bayesian networks is given based on whether or not they are prime for all state vectors. A proof of the Degree-2 Conjecture is given for a subclass of Bayesian networks which includes those with binomial global Markov ideal.

Date Issued
2006-07-27T12:35:34Z
Keywords
computational algebra
•
bayesian networks
•
algebraic geometry
•
determinantal ideals
Type
dissertation or thesis

Site Statistics | Help

About eCommons | Policies | Terms of use | Contact Us

copyright © 2002-2026 Cornell University Library | Privacy | Web Accessibility Assistance