Method of Fast Bandwidth Selection in a Nonparametric Classifier Corresponding to the a Posteriori Probability Maximum Criterion


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Abstract

A method of fast bandwidth selection in a nonparametric algorithm of pattern recognition corresponding to the maximum a posteriori probability criterion is proposed. The algorithm is based on the results of studying the asymptotic properties of the nonparametric estimate of the separation surface equation and probability densities in solving a two-alternative problem of pattern recognition. The proposed method is compared with the traditional approach based on minimizing the classification error probability estimate.

About the authors

A. V. Lapko

Institute of Computational Modeling, Siberian Branch; Reshetnev Siberian University of Science and Technology

Author for correspondence.
Email: lapko@icm.krasn.ru
Russian Federation, Akademgorodok 50, building 44, Krasnoyarsk, 660036; pr. im. gazety “Krasnoyarskii rabochii” 31, Krasnoyarsk, 660037

V. A. Lapko

Institute of Computational Modeling, Siberian Branch; Reshetnev Siberian University of Science and Technology

Email: lapko@icm.krasn.ru
Russian Federation, Akademgorodok 50, building 44, Krasnoyarsk, 660036; pr. im. gazety “Krasnoyarskii rabochii” 31, Krasnoyarsk, 660037

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