Bayesian Chain Classifiers for Multidimensional Classification

  title={Bayesian Chain Classifiers for Multidimensional Classification},
  author={Julio H. Zaragoza and Luis Enrique Sucar and Eduardo F. Morales and Concha Bielza and Pedro Larra{\~n}aga},
In multidimensional classification the goal is to assign an instance to a set of different classes. This task is normally addressed either by defining a compound class variable with all the possible combinations of classes (label power-set methods, LPMs) or by building independent classifiers for each class (binary-relevance methods, BRMs). However, LPMs do not scale well and BRMs ignore the dependency relations between classes. We introduce a method for chaining binary Bayesian classifiers… CONTINUE READING
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