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In this paper we address the problem of discretization in the context oflearning Bayesian networks (BNs) from data containing both continuous anddiscrete variables. We describe a new technique for <EM>multivariate</EM>discretization, whereby each continuous variable is discretized while takinginto account its interaction with the other variables. The technique is basedon the use of a Bayesian scoring metric that scores the discretization policyfor a continuous variable given a BN structure and the observed data. Since themetric is relative to the BN structure currently being evaluated, thediscretization of a variable needs to be dynamically adjusted as the BNstructure changes.

A Multivariate Discretization Method for Learning Bayesian Networks from Mixed Data