Probabilistic and Bayesian Networks

Ke-Lin Du () and M. N. S. Swamy
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Ke-Lin Du: Concordia University, Department of Electrical and Computer Engineering
M. N. S. Swamy: Concordia University, Department of Electrical and Computer Engineering

Chapter Chapter 22 in Neural Networks and Statistical Learning, 2019, pp 645-698 from Springer

Abstract: Abstract This chapter introduces several important probabilistic models. Bayesian network is a well-known probabilistic model in machine learning. Hidden Markov model is a special case of Bayesian network model for dynamic systems. Important probabilistic methods, including sampling methods, expectation–maximization method, variational Bayesian method, and mixture method, are introduced. Some Bayesian and probabilistic approaches to machine learning are also mentioned in this chapter.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4471-7452-3_22

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DOI: 10.1007/978-1-4471-7452-3_22

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