Bayesian and Decision Models in AI

Seminar:

• Cognitive Science and Bayes: to Bayes or not to Bayes [Slides PDF, or Gzipped Postscript]

• Use of genetic algorithms in BN structure learning [Slides PDF, or Gzipped Postscript]

Content of Practicals:

• Assignment I: build your own Bayesian network
• Assignment II: learning Bayesian networks:
  • Database 1: alarm dataset with 10000 records
  • Database 2: data of patients with non-Hodgkin lymphoma (NA is missing value)
  • Database 3: data of patients with breast cancer

Tutorials:

• Tutorial I [PDF; gzipped PS]: concerning probability theory and Baysian networks (for 19th February, 2009)

• Tutorial II [PDF; gzipped PS]: Baysian networks (for 5th March, 2009)

• Tutorial III [PDF; gzipped PS]: Markov independence (for 12th March, 2009); Solutions

• Tutorial IV: Markov independence (rest of tutorial III exercises) (for 19th March, 2009)

• Tutorial V [PDF; gzipped PS]: Pearl's algorithm (for 26th March, 2009)