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Learning Bayesian network parameters via minimax algorithm.

, , , , , и . Int. J. Approx. Reason., (2019)

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Xiao-Guang Yang

Guang-hui Xiao

Xiao-Guang Chen

Guang Rao

Guang Bai

 

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Learning Bayesian networks using the constrained maximum a posteriori probability method., , , и . Pattern Recognit., (2019)Approximate inference for dynamic Bayesian networks: sliding window approach., , , и . Appl. Intell., 40 (4): 575-591 (2014)Structure Learning of Bayesian Networks by Finding the Optimal Ordering., , и . ICPR, стр. 177-182. IEEE Computer Society, (2018)Microshell Arrays Enhanced Sensitivity in Detection of Specific Antibody for Reduced Graphene Oxide Optical Sensor., , , , , , , и . Sensors, 17 (2): 221 (2017)Learning Bayesian network parameters via minimax algorithm., , , , , и . Int. J. Approx. Reason., (2019)A solving algorithm for Target Assignment optimization model based on ACO., , , и . ICNC, стр. 3753-3757. IEEE, (2010)Learning Bayesian Network Parameters from Small Data Set: A Spatially Maximum a Posteriori Method., , , и . AMBN@JSAI-isAI, том 9505 из Lecture Notes in Computer Science, стр. 32-45. Springer, (2015)Bayesian approach to learn Bayesian networks using data and constraints., , , и . ICPR, стр. 3667-3672. IEEE, (2016)Learning Bayesian network parameters from small data sets: A further constrained qualitatively maximum a posteriori method., , , , , и . Int. J. Approx. Reason., (2017)