Corpus ID: 1011569

Learning Bayesian Networks: Search Methods and Experimental Results

@inproceedings{Chickering1995LearningBN,
  title={Learning Bayesian Networks: Search Methods and Experimental Results},
  author={M. Chickering and D. Geiger and D. Heckerman},
  year={1995}
}
We discuss Bayesian approaches for learning Bayesian networks from data. First, we review a metric for computing the relative posterior probability of a network structure given data developed by Heckerman et al. (1994a,b,c). We see that the metric has a property useful for inferring causation from data. Next, we describe search methods for identifying network structures with high posterior probabilities. We describe polynomial algorithms for nding the highestscoring network structures in the… Expand
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