Semi-supervised SVM with Fuzzy Controlled Cooperation of Biology Related Algorithms

Shakhnaz Akhmedova, Eugene Semenkin, Vladimir Stanovov

Abstract

Due to its wide applicability, the problem of semi-supervised classification is attracting increasing attention in machine learning. Semi-Supervised Support Vector Machines (SVM) are based on applying the margin maximization principle to both labelled and unlabelled examples. A new collective bionic algorithm, namely fuzzy controlled cooperation of biology related algorithms (COBRA-f), which solves constrained optimization problems, has been developed for semi-supervised SVM design. Firstly, the experimental results obtained by the two types of fuzzy controlled COBRA are presented and compared and their usefulness is demonstrated. Then the performance and behaviour of proposed semi-supervised SVMs are studied under common experimental settings and their workability is established.

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Paper Citation


in Harvard Style

Akhmedova S., Semenkin E. and Stanovov V. (2017). Semi-supervised SVM with Fuzzy Controlled Cooperation of Biology Related Algorithms . In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-263-9, pages 64-71. DOI: 10.5220/0006417400640071


in Bibtex Style

@conference{icinco17,
author={Shakhnaz Akhmedova and Eugene Semenkin and Vladimir Stanovov},
title={Semi-supervised SVM with Fuzzy Controlled Cooperation of Biology Related Algorithms},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2017},
pages={64-71},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006417400640071},
isbn={978-989-758-263-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Semi-supervised SVM with Fuzzy Controlled Cooperation of Biology Related Algorithms
SN - 978-989-758-263-9
AU - Akhmedova S.
AU - Semenkin E.
AU - Stanovov V.
PY - 2017
SP - 64
EP - 71
DO - 10.5220/0006417400640071