Randomization and Entropy in Machine Learning and Data Processing

Combining the concept of randomization with entropic criteria allows solutions to be obtained in the conditions of maximum uncertainty, which is very effective in machine learning and data processing. The application of this approach in data-based entropy-randomized evaluation of functions, randomiz...

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Bibliographic Details
Published in:Doklady. Mathematics 2022-06, Vol.105 (3), p.135-157
Main Author: Popkov, Yu. S.
Format: Article
Language:English
Subjects:
Clustering
Data processing
Detailed Publications
Electrical loads
Entropy
Machine learning
Mathematics
Mathematics and Statistics
Randomization
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Summary:Combining the concept of randomization with entropic criteria allows solutions to be obtained in the conditions of maximum uncertainty, which is very effective in machine learning and data processing. The application of this approach in data-based entropy-randomized evaluation of functions, randomized hard and soft machine learning, object clustering, and data matrix dimension reduction is demonstrated. Some applications of classification problems, forecasting the electric load of a power system, and randomized clustering of biological objects are considered.
ISSN:1064-5624
1531-8362
DOI:10.1134/S1064562422030073