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The Classification of Noisy Sequences Generated by Similar HMMs

  • A. A. Popov
  • T. A. Gultyaeva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6744)

Abstract

The method for classification performance improvement using hidden Markov models (HMM) is proposed. The k-nearest neighbors (kNN) classifier is used in the feature space produced by these HMM. Only the similar models with the noisy original sequences assumption are discussed. The research results on simulated data for two-class classification problem are presented.

Keywords

Hidden Markov Model Derivation k Nearest Neighbors 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • A. A. Popov
    • 1
  • T. A. Gultyaeva
    • 1
  1. 1.Department of Software and Database EngineeringNovosibirsk State Technical UniversityRussia

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