Why learn a Bayesian network?

• Combine knowledge engineering and statistical induction

  • Covers the whole spectrum from knowledge-intensive model construction to data-intensive model induction

• More than a learning black-box

  • Explanation of outputs
  • Interpretability and modifiability
  • Algorithms for decision making, value of information, diagnosis and repair

• Causal representation, reasoning, and discovery

  • Does smoking cause cancer?

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