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Bayesian Decision Theory: Course Outline

Bayesian decision theory is a fundamental statistical approach to the problem of pattern classification.

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Course Outline

  • Utility theory. 
  • The utility of money.
  • Rewards, Consequences.
  • The loss functions.
  • Development of the loss function from the utility theory.
  • Certain standard loss functions for inference and predictive problems. 
  • Bayes estimators. 
  • Bayes predictors.
  • Bayesian hypothesis testing under the different loss functions.
  • Decision function. 
  • Multivariate loss function with Bayesian estimation. 
  • Risk.
  • Types of risk. 
  • Choice of a sample size under posterior Bayes risk.

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