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Bayesian decision making: advanced level

The educational material for advanced users is organized so that to show both the theoretical and practical sides of Bayesian decision-making. The examples of the solutions in this sections are mostly implemented either with the help of Mixtools or with Mixtools3000. According the projects where the decision-making tasks have been implemented the educational material has the following structure:

  • Mixtures (application of Mixtools)
    • Learning with normal mixtures
    • Design with normal mixtures
    • Application in medicine
  • Multi-participant Decision Making (application of Mixtools3000)
  • Fully probabilistic Design (application of Mixtools3000)


Local SVN repository (accessible with password only):