The von Mises naive Bayes classifier for angular data

Authors:
Pedro L. López-Cruz;Concha Bielza;Pedro Larrañaga
Affiliations:
Computational Intelligence Group, Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain;Computational Intelligence Group, Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain;Computational Intelligence Group, Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain
Venue:
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
Year:
2011

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Abstract

Directional and angular information are to be found in almost every field of science. Directional statistics provides the theoretical background and the techniques for processing such data, which cannot be properly managed by classical statistics. The von Mises distribution is the best known angular distribution. We extend the naive Bayes classifier to the case where directional predictive variables are modeled using von Mises distributions. We find the decision surfaces induced by the classifiers and illustrate their behavior with artificial examples. Two applications to real data are included to show the potential uses of these models. Comparisons with classical techniques yield promising results.