Construction of Large-Scale Bayesian Networks by Local to Global Search
2002; Springer Science+Business Media; Linguagem: Inglês
10.1007/3-540-45683-x_41
ISSN1611-3349
AutoresKyu-Baek Hwang, Jae‐Won Lee, Seung-Woo Chung, Byoung‐Tak Zhang,
Tópico(s)Rough Sets and Fuzzy Logic
ResumoMost existing algorithms for structural learning of Bayesian networks are suitable for constructing small-sized networks which consist of several tens of nodes. In this paper, we present a novel approach to the efficient and relatively-precise induction of large-scale Bayesian networks with up to several hundreds of nodes. The approach is based on the concept of Markov blanket and makes use of the divide-and-conquer principle. The proposed method has been evaluated on two benchmark datasets and a real-life DNA microarray data, demonstrating the ability to learn the large-scale Bayesian network structure efficiently.
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