Evolutionary Structure Learning Algorithm for Bayesian Network and Penalized Mutual Information Metric

Authors:
Gang Li;Fu Tong;Honghua Dai
Affiliations:
-;-;-
Venue:
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Year:
2001

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Abstract

This paper formulates the problem of learning Bayesian network structures from data as determining the structure that best approximates the probability distribution indicated by the data. A new metric, Penalized Mutual Information metric, is proposed, and a evolutionary algorithm is designed to search for the best structure among alternatives. The experimental results show that this approach is reliable and promising.