Discovery of Context-Specific Markov Blankets

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The notion of Context-Specific Markov Blankets (CSMB) is a refinement of Markov Blankets (MB). An important property of context specific Markov-Blankets is that in the worst case they need as many parameters as a model using a standard Markov blanket, but frequently considerably fewer. The result is expected to be a much improved probabilistic model of the data in practice. An algorithm for discovery of the CSMB is presented, and empirical results show that it is capable of successfully recovering context specific ("local") structures.

Original languageEnglish
Title of host publication2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
Pages3833-3838
Number of pages6
DOIs
StatePublished - 1 Dec 2004
Event2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 - The Hague, Netherlands
Duration: 10 Oct 200413 Oct 2004

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume4
ISSN (Print)1062-922X

Conference

Conference2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
Country/TerritoryNetherlands
CityThe Hague
Period10/10/0413/10/04

Keywords

  • Bayesian Knowledge Bases
  • Bayesian Networks
  • Context specific independence
  • Data Mining
  • Markov Blankets

Fingerprint

Dive into the research topics of 'Discovery of Context-Specific Markov Blankets'. Together they form a unique fingerprint.

Cite this