Wallenius Naïve Bayes

  • Enric Junque de Fortuny
  • David Martens
  • Foster Provost

Traditional event models underlying naive Bayes classifiers assume probability distributions that are not appropriate for binary data generated by human behaviour.  In this work, we develop a new event model, based on a somewhat forgotten distribution created by Kenneth Ted Wallenius in 1963.  We show that it achieves superior performance using less data on a collection of Facebook datasets, where the task is to predict personality traits, based on likes.

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