Classifier Learning with Supervised Marginal Likelihood

  title={Classifier Learning with Supervised Marginal Likelihood},
  author={Petri Kontkanen and Petri Myllym{\"a}ki and Henry Tirri},
It has been argued that in supervised classification tasks it may be more sensible to perform model selection with respect to a more focused model selection score, like the supervised (conditional) marginal likelihood, than with respect to the standard unsupervised marginal likelihood criterion. However, for most Bayesian network models, computing the supervised marginal likelihood score takes exponential time with respect to the amount of observed data. In this paper, we consider diagnostic… CONTINUE READING
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