The von Mises Naive Bayes Classifier for Angular Data

  • Pedro L. López-Cruz
  • Concha Bielza
  • Pedro Larrañaga
Conference paper

DOI: 10.1007/978-3-642-25274-7_15

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7023)
Cite this paper as:
López-Cruz P.L., Bielza C., Larrañaga P. (2011) The von Mises Naive Bayes Classifier for Angular Data. In: Lozano J.A., Gámez J.A., Moreno J.A. (eds) Advances in Artificial Intelligence. CAEPIA 2011. Lecture Notes in Computer Science, vol 7023. Springer, Berlin, Heidelberg

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.

Keywords

Naive Bayes classifier supervised classification circular statistics directional statistics angular data von Mises distribution 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Pedro L. López-Cruz
    • 1
  • Concha Bielza
    • 1
  • Pedro Larrañaga
    • 1
  1. 1.Computational Intelligence Group Departamento de Inteligencia Artificial Facultad de InformáticaUniversidad Politécnica de MadridBoadilla del MonteSpain

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