A decomposition hybrid structure learning algorithm for Bayesian network using expert knowledge
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software
Link
https://link.springer.com/content/pdf/10.1007/s10115-023-01843-4.pdf
Reference30 articles.
1. Alonso J, Ossa L, Gámez J, Puerta J (2018) On the use of local search heuristics to improve GES-based Bayesian network learning. Appl Soft Comput 64:366–376. https://doi.org/10.1016/j.asoc.2017.12.011
2. Amirkhani H, Rahmati M, Lucas PJF, Hommersom A (2017) Exploiting experts’ knowledge for structure learning of Bayesian networks. IEEE T Pattern Anal 39:2154–2170. https://doi.org/10.1109/TPAMI.2016.2636828
3. Behjati S, Beigy H (2020) Improved K2 algorithm for Bayesian network structure learning. Eng Appl Artif Intel 103617:1–12. https://doi.org/10.1016/j.engappai.2020.103617
4. Buntine W (1991) Theory Refinement on Bayesian Networks. In: Proceedings of the Seventh Conference, Morgan Kaufmann, pp 52–60
5. Castelo R, Roverato A (2006) A robust procedure for gaussian graphical model search from microarray data with p larger than n. J Mach Learn Res 6:2621–2650
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