IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Network Refinement Via Machine Learning Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evolutionary Optimization in Dynamic Environments
Evolutionary Optimization in Dynamic Environments
Coevolutionary, Distributed Search for Inducing Concept Description
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Abstention Reduces Errors - decision Abstaining N-version Genetic Programming
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
The Evolution of Causal Models: A Comparison of Bayesian Metrics and Structure Priors
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
Data mining of Bayesian networks using cooperative coevolution
Decision Support Systems
Learning Bayesian Networks
Learning Bayesian network structures by searching for the best ordering with genetic algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Comparison of score metrics for Bayesian network learning
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A review on evolutionary algorithms in Bayesian network learning and inference tasks
Information Sciences: an International Journal
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Recently, there are many researchers to design Bayesian network structures using evolutionary algorithms but most of them use the only one fittest solution in the last generation. Because it is difficult to integrate the important factors into a single evaluation function, the best solution is often biased and less adaptive. In this paper, we present a method of generating diverse Bayesian network structures through fitness sharing and combining them by Bayesian method for adaptive inference. In the experiments with Asia network, the proposed method provides with better robustness for handling uncertainty owing to the complicated redundancy with speciated evolution.