10-601 GM1

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This a lecture used in the Syllabus for Machine Learning 10-601 in Fall 2014

Slides

Readings

  • Chapter 6.11 Mitchell
  • Chapter 10 Murphy
  • Or: Chap 8.1 and 8.2.2 (Bishop)

Taking home message

  • factorization theorem of BN
  • Full, independent and intermediate conditional probability models
  • Markov blanket
  • Learning a BN
  • Inference in BN is NP hard
  • Approximate inference in BN
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