Entropy-Based Estimation in Classification Problems
- 作者: Dubnov Y.A.1,2,3
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隶属关系:
- 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
- 期: 卷 80, 编号 3 (2019)
- 页面: 502-512
- 栏目: Intellectual Control Systems, Data Analysis
- URL: https://journals.rcsi.science/0005-1179/article/view/151330
- DOI: https://doi.org/10.1134/S0005117919030093
- ID: 151330
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详细
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.
作者简介
Yu. 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
编辑信件的主要联系方式.
Email: yury.dubnov@phystech.edu
俄罗斯联邦, Moscow; Moscow; Moscow
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