Bayesian network structure learning by recursive autonomy identification

Raanan Yehezkel, Boaz Lerner

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

2 Scopus citations

Abstract

We propose the recursive autonomy identification (RAI) algorithm for constraint-based Bayesian network structure learning. The RAI algorithm learns the structure by sequential application of conditional independence (CI) tests, edge direction and structure decomposition into autonomous substructures. The sequence of operations is performed recursively for each autonomous sub-structure while simultaneously increasing the order of the CI test. In comparison to other constraint-based algorithms d-separating structures and then directing the resulted undirected graph, the RAI algorithm combines the two processes from the outset and along the procedure. Thereby, learning a structure using the RAI algorithm requires a smaller number of high order CI tests. This reduces the complexity and run-time as well as increases structural and prediction accuracies as demonstrated in extensive experimentation.

Original languageEnglish
Title of host publicationStructural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops, SSPR 2006 and SPR 2006, Proceedings
PublisherSpringer Verlag
Pages154-162
Number of pages9
ISBN (Print)3540372369, 9783540372363
DOIs
StatePublished - 1 Jan 2006
EventJoint IAPR International Workshops on Structural, Syntactic, and Statistical Pattern Recognition, SSPR 2006 and SPR 2006 - Hong Kong, China
Duration: 17 Aug 200619 Aug 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4109 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceJoint IAPR International Workshops on Structural, Syntactic, and Statistical Pattern Recognition, SSPR 2006 and SPR 2006
Country/TerritoryChina
CityHong Kong
Period17/08/0619/08/06

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