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In this paper, a new hybrid incremental learning algorithm for Bayesian network structures is proposed. It develops a polynomial-time constraint-based technique to build up a candidate parents set for each domain variable, and a hill climbing search procedure is then employed to refine the current network structure under the guidance of those candidate parents sets. Our algorithm always offers considerable...
Hybrid learning can reduce the computational complexity of incremental algorithms for Bayesian network structures significantly. In this paper, a group of hybrid incremental algorithms are proposed. The central idea of these algorithms is to use the polynomial-time constraint-based technique to build a candidate parent set for each domain variable, followed by the hill climbing search procedure to...
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