Semi-supervised Learning Based on Graph Stochastic Co-Training

Authors

  • Victor Sineglazov National Aviation University, Kyiv, Ukraine https://orcid.org/0000-0002-3297-9060
  • Serhii Yarovyi National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

DOI:

https://doi.org/10.18372/1990-5548.77.18001

Keywords:

multiclass classification, semi-supervised learning, single-view co-training, stochastic label propagation

Abstract

This article is devoted to the development of a new approach in semi-supervised machine learning. The goal of this article is to analyze the accuracy of the single-view co-training system, based on the use of a modified graph-based stochastic label propagation algorithm for a multiclass classification problem. Graph transformation of data is preceded by feature decomposition, with three algorithms being compared: Singular Value Decomposition, Truncated Singular Value Decomposition, Iterative Primary Component Analysis, Kernel Primary Component Analysis. To improve the accuracy of the proposed method, additional parameter was included in the label propagation algorithm, allowing for the usage of the algorithm in co-training systems. Further performance increases are achieved via optimization of data modification, which is achieved by applying feature decomposition methods and parallelizing the calculation-heavy processes. As examples of practical use were considered solutions to the problem of multiclass classification for standard datasets of the library sklearn and for the real dataset Traffic Signs Preprocessed. Analyses of the results of the implementation of the proposed approach showed improvements in accuracy and of performance solving the multiclass classification problem.

Author Biographies

Victor Sineglazov , National Aviation University, Kyiv, Ukraine

Doctor of Engineering Science

Professor

Head of the Department of Aviation Computer-Integrated Complexes

Faculty of Air Navigation Electronics and Telecommunications

Serhii Yarovyi , National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

Masters Student

Department of Artificial Intelligence

Institute for Applied System Analysis

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Published

2023-09-27

How to Cite

Sineglazov , V., & Yarovyi , S. (2023). Semi-supervised Learning Based on Graph Stochastic Co-Training. Electronics and Control Systems, 3(77), 9–16. https://doi.org/10.18372/1990-5548.77.18001

Issue

Vol. 3 No. 77 (2023)

Section

COMPUTER SCIENCES AND INFORMATION TECHNOLOGIES

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