Learning Bayesian Networks : Search Methods and Experimental Results

  title={Learning Bayesian Networks : Search Methods and Experimental Results},
  author={David Maxwell Chickering and Dan Geiger},
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… CONTINUE READING
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