Algorithm for graphical Bayesian modeling based on multiple regressions

Authors:
Ádamo L. De Santana;Carlos Renato L. Francês;João C. Weyl Costa
Affiliations:
Laboratory of High Performance Networks Planning, Federal University of Para, Belem, PA, Brazil;Laboratory of High Performance Networks Planning, Federal University of Para, Belem, PA, Brazil;Laboratory of High Performance Networks Planning, Federal University of Para, Belem, PA, Brazil
Venue:
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Year:
2007

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Abstract

One of the main factors for the knowledge discovery success is related to the comprehensibility of the patterns discovered by applying data mining techniques. Amongst which we can point out the Bayesian networks as one of the most prominent when considering the easiness of knowledge interpretation achieved. Bayesian networks, however, present limitations and disadvantages regarding their use and applicability. This paper presents an extension for the improvement of Bayesian networks, incorporating models of multiple regression for structure learning.