Bayesian online classification using Rao-Blackwellised SMC and its application

Tomohiro Kudo, Yohei Nakada, Takashi Matsumoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a Bayesian online classification method using Rao-Blackwellised Sequential Monte Carlo. The method is validated by testing it against a numerical example. As an example of a real-world application, the method is also applied to a computer intrusion detection problem. The proposed method has succeeded in reducing the false alarm rate when compared with a previous work.

Original languageEnglish
Title of host publicationProceedings of the 4th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2007
Pages222-227
Number of pages6
Publication statusPublished - 1 Dec 2007
Event4th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2007 - Innsbruck, Austria
Duration: 14 Feb 200716 Feb 2007

Publication series

NameProceedings of the 4th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2007

Conference

Conference4th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2007
CountryAustria
CityInnsbruck
Period14/02/0716/02/07

    Fingerprint

Keywords

  • Computer intrusion detection
  • On-line Bayesian learning
  • On-line classification
  • Rao-Blackwellised Sequential Monte Carlo

Cite this

Kudo, T., Nakada, Y., & Matsumoto, T. (2007). Bayesian online classification using Rao-Blackwellised SMC and its application. In Proceedings of the 4th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2007 (pp. 222-227). (Proceedings of the 4th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA 2007).