Learning
BN models can be learned from empirical data
- parameter estimation via numerical optimization
- structure learning via combinatorial search.
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Probabilistic framework provides many useful tools
- scoring function over hypotheses
- rigorous ways for dealing with missing data (EM).
BN structures define hypothesis space
- bias towards hypotheses with independence structure.