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Bayesian Theory of Decision

  • Francesco CamastraEmail author
  • Alessandro Vinciarelli
Chapter
Part of the Advanced Information and Knowledge Processing book series (AI&KP)

Abstract

What the reader should know to understand this chapter\(\bullet \) Basic notions of statistics and probability theory (see Appendix A). \(\bullet \) Calculus notions are an advantage.

Keywords

Decision Rule False Positive Rate Loss Function Discriminant Function Prior Probability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.Department of Science and TechnologyParthenope University of NaplesNaplesItaly
  2. 2.School of Computing Science and the Institute of Neuroscience and PsychologyUniversity of GlasgowGlasgowUK

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