Entropy-Based Estimation in Classification Problems

被引：0
|
作者：
Yu. A. Dubnov
机构：
[1] Institute for Systems Analysis of the “Computer Science and Control” Federal Research Center of the Russian Academy of Sciences,
[2] National Research University Higher School of Economics,undefined
[3] Moscow Institute (State University) of Physics and Technology,undefined
来源：
Automation and Remote Control | 2019年 / 80卷
关键词：
machine learning; classification; maximum entropy method;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：502 / 512
页数：10
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