On Pairwise Naive Bayes Classifiers

  title={On Pairwise Naive Bayes Classifiers},
  author={Jan-Nikolas Sulzmann and Johannes F{\"u}rnkranz and Eyke H{\"u}llermeier},
Class binarizations are effective methods for improving weak learners by decomposing multi-class problems into several two-class problems. This paper analyzes how these methods can be applied to a Naive Bayes learner. The key result is that the pairwise variant of Naive Bayes is equivalent to a regular Naive Bayes. This result holds for several aggregation techniques for combining the predictions of the individual classifiers, including the commonly used voting and weighted voting techniques… CONTINUE READING
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