The classification of noisy sequences generated by similar HMMs

Authors:
A. A. Popov;T. A. Gultyaeva
Affiliations:
Department of Software and Database Engineering, Novosibirsk State Technical University, Russia;Department of Software and Database Engineering, Novosibirsk State Technical University, Russia
Venue:
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
Year:
2011

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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.