Email this article Entropy-Based Estimation in Classification Problems
- Authors: Dubnov Y.A.1,2,3
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Affiliations:
- Institute for Systems Analysis of the “Computer Science and Control” Federal Research Center of the Russian Academy of Sciences
- National Research University Higher School of Economics
- Moscow Institute (State University) of Physics and Technology
- Issue: Vol 80, No 3 (2019)
- Pages: 502-512
- Section: Intellectual Control Systems, Data Analysis
- URL: https://ogarev-online.ru/0005-1179/article/view/151330
- DOI: https://doi.org/10.1134/S0005117919030093
- ID: 151330
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Abstract
The problem of binary classification is considered, an algorithm for its solution is proposed, based on the method of entropy-based estimation of the decision rule parameters. A detailed description of the entropy-based estimation method and the classification algorithm is given, the advantages and disadvantages of this approach are described, the results of numerical experiments and comparisons with the traditional support vector machine for classification accuracy and degree of dependence on the training sample size are presented.
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About the authors
Yu. A. Dubnov
Institute for Systems Analysis of the “Computer Science and Control” Federal Research Center of the Russian Academy of Sciences; National Research University Higher School of Economics; Moscow Institute (State University) of Physics and Technology
Author for correspondence.
Email: yury.dubnov@phystech.edu
Russian Federation, Moscow; Moscow; Moscow
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