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Artificial Intelligence and Decision Making, 2020, Issue 2, Pages 78–85
DOI: https://doi.org/10.14357/20718594200206
(Mi iipr136)
 

Decision analysis

Feature selection method based on a probabilistic approach and cross-entropy metric for image recognition problem

Yu. A. Dubnovab

a Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow, Russia
b HSE University, Moscow, Russia
Abstract: The paper considers the problem of feature selection in the classification problem. A method for selecting informative features based on a probabilistic approach and cross-entropy metrics is proposed. Several variants of the information criterion for selecting features for a binary classification problem are considered, as well as its generalization to the case of a multiclass problem. Demonstration examples of the proposed method for the task of image recognition from the mnist collection are given.
Keywords: feature selection, classification, cross-entropy.
Funding agency Grant number
Russian Foundation for Basic Research 17-07-00286
17-29-03119
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: Yu. A. Dubnov, “Feature selection method based on a probabilistic approach and cross-entropy metric for image recognition problem”, Artificial Intelligence and Decision Making, 2020, no. 2, 78–85
Citation in format AMSBIB
\Bibitem{Dub20}
\by Yu.~A.~Dubnov
\paper Feature selection method based on a probabilistic approach and cross-entropy metric for image recognition problem
\jour Artificial Intelligence and Decision Making
\yr 2020
\issue 2
\pages 78--85
\mathnet{http://mi.mathnet.ru/iipr136}
\crossref{https://doi.org/10.14357/20718594200206}
\elib{https://elibrary.ru/item.asp?id=43023333}
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