A Stable Stochastic Optimization Algorithm for Triangulation of Bayesian Networks

Authors:
Xuchu Dong;Dantong Ouyang;Yuxin Ye;Shasha Feng;Haihong Yu
Affiliations:
-;-;-;-;-
Venue:
WKDD '10 Proceedings of the 2010 Third International Conference on Knowledge Discovery and Data Mining
Year:
2010

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Abstract

In this paper, we present a novel deterministic heuristic and a new genetic algorithm to solve the problem of optimal triangulation of Bayesian networks. The heuristic, named MinFillWeight, aims to select variables minimizing the multiplication of the weights on nodes of fill-in edges. The genetic algorithm, named GA-MFW, uses a new rank-reserving crossover operator and a 2-fold mutation mechanism utilizing the MinFillWeight heuristic. Experiments on representative benchmark show that the deterministic heuristic and the stochastic algorithm have good performance and stability to various problems.