1 Bayes' Decision Theory

Speech Processing ◽

10.1201/9781482276237-35 ◽

2018 ◽

pp. 206-207

Keyword(s):

Decision Theory ◽

Bayes Decision Theory

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Data-Driven Classifier for Extreme Outage Prediction Based on Bayes Decision Theory

IEEE Transactions on Power Systems ◽

10.1109/tpwrs.2021.3086031 ◽

2021 ◽

pp. 1-1

Author(s):

Mohammad Shahidehpour ◽

Mostafa Mohammadian ◽

Farrokh Aminifar ◽

Nima Amjady

Keyword(s):

Decision Theory ◽

Data Driven ◽

Bayes Decision Theory

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Model selection and fault detection approach based on Bayes decision theory: Application to changes detection problem in a distillation column

Process Safety and Environmental Protection ◽

10.1016/j.psep.2013.02.004 ◽

2014 ◽

Vol 92 (3) ◽

pp. 215-223 ◽

Author(s):

Yahya Chetouani

Keyword(s):

Model Selection ◽

Fault Detection ◽

Decision Theory ◽

Distillation Column ◽

Detection Problem ◽

Detection Approach ◽

Theory Application ◽

Changes Detection ◽

Bayes Decision Theory

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A class of distortionless codes designed by Bayes decision theory

IEEE Transactions on Information Theory ◽

10.1109/18.133247 ◽

1991 ◽

Vol 37 (5) ◽

pp. 1288-1293 ◽

Author(s):

T. Matsushima ◽

H. Inazumi ◽

S. Hirasawa

Keyword(s):

Decision Theory ◽

Bayes Decision Theory

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Classifiers Based on Bayes Decision Theory

Pattern Recognition ◽

10.1016/b978-1-59749-272-0.50004-9 ◽

2009 ◽

pp. 13-89 ◽

Author(s):

Sergios Theodoridis ◽

Konstantinos Koutroumbas

Keyword(s):

Decision Theory ◽

Bayes Decision Theory

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Credible Interval Prediction of a Nonstationary Poisson Distribution based on Bayes Decision Theory

Proceedings of the 12th International Conference on Agents and Artificial Intelligence ◽

10.5220/0009182209951002 ◽

2020 ◽

Author(s):

Daiki Koizumi

Keyword(s):

Decision Theory ◽

Poisson Distribution ◽

Credible Interval ◽

Interval Prediction ◽

Bayes Decision Theory

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Multilayer neural networks and Bayes decision theory

Neural Networks ◽

10.1016/s0893-6080(97)00120-2 ◽

1998 ◽

Vol 11 (2) ◽

pp. 209-213 ◽

Author(s):

Ken-ichi Funahashi

Keyword(s):

Neural Networks ◽

Decision Theory ◽

Bayes Decision Theory ◽

Multilayer Neural Networks

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Time series classification using the Volterra connectionist model and Bayes decision theory

IEEE International Conference on Acoustics Speech and Signal Processing ◽

10.1109/icassp.1993.319190 ◽

1993 ◽

Author(s):

J.J. Rajan ◽

P.J.W. Rayner

Keyword(s):

Time Series ◽

Decision Theory ◽

Connectionist Model ◽

Time Series Classification ◽

Bayes Decision Theory

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Bayes Decision Theory

Encyclopedia of Biometrics ◽

10.1007/978-0-387-73003-5_741 ◽

2009 ◽

pp. 61-61

Keyword(s):

Decision Theory ◽

Bayes Decision Theory

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Convex Bayes decision theory

IEEE Transactions on Systems Man and Cybernetics ◽

10.1109/21.101147 ◽

1991 ◽

Vol 21 (1) ◽

pp. 173-183 ◽

Author(s):

W.C. Stirling ◽

D.R. Morrell

Keyword(s):

Decision Theory ◽

Bayes Decision Theory

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Mixture catastrophes and Bayes decision theory

Mathematical Proceedings of the Cambridge Philosophical Society ◽

10.1017/s0305004100000669 ◽

1979 ◽

Vol 86 (1) ◽

pp. 91-101 ◽

Author(s):

J. Q. Smith

Keyword(s):

Qualitative Study ◽

Decision Theory ◽

Decision Maker ◽

Loss Function ◽

Catastrophe Theory ◽

Loss Functions ◽

Expected Loss ◽

Bayes Decision Theory ◽

Class Of Functions

To make a Bayes decision we choose the infimum of an expected loss function. Catastrophe theory classifies a wide class of functions locally in terms of their critical values. Firstly we will show how this local classification relates globally to some mixtures of symmetric expected loss functions. Secondly we shall indicate how such mixtures can arise and how the above classification can be usefully applied to the qualitative study of the behaviour of a Bayes decision-maker.

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