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Please use this identifier to cite or link to this item: https://elib.bsu.by/handle/123456789/233399
Title: Principle components method in statistical classification and its efficiency
Authors: Zhuk, E. E.
Keywords: ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика
ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика
Issue Date: 2019
Publisher: Minsk : BSU
Citation: Computer Data Analysis and Modeling: Stochastics and Data Science : Proc. of the Twelfth Intern. Conf., Minsk, Sept. 18-22, 2019. – Minsk : BSU, 2019. – P. 337-340.
Abstract: The problem of reducing the dimensionality in statistical classification is studied. The case of the well-known Fisher model of multivariate normal (Gaussian) distribution mixture is considered. The average decrease of interclass distances square is presented as a new criterion of feature selection directly connected with the classification error probability. The stepwise discriminant analysis procedure based on this criterion is proposed
URI: http://elib.bsu.by/handle/123456789/233399
ISBN: 978-985-566-811-5
Appears in Collections:2019. Computer Data Analysis and Modeling : Stochastics and Data Science

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