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A rough margin-based ν-twin support vector machine

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Abstract

Twin support vector machine (TSVM) is a new machine learning algorithm, which aims at finding two nonparallel planes for each class. In order to do so, one needs to resolve a pair of smaller-sized quadratic programming problems (QPPs) rather than a single large one. However, when constructing the classification plane for one class, a large number of samples of this class are considered in the objective function, but only fewer samples in the other class are considered, which easily results in over-fitting problem. In addition, the same penalties are given to each misclassified samples in the TSVM. In fact, the misclassified samples have different effects on the decision of the hyper-plane. In order to overcome these two disadvantages, by introducing the rough set theory into ν-TSVM, we propose a rough margin-based ν-TSVM in this paper. In the proposed algorithm, the different points in the different positions are proposed to have different effects on the separating hyper-plane. We firstly construct rough lower margin, rough upper margin, and rough boundary in the ν-TSVM and then give the different penalties to the different misclassified samples according to their positions. The new classifier can avoid the over-fitting problem to a certain extent. Numerical experiments on one artificial dataset and six benchmark datasets demonstrate the feasibility and validity of the proposed algorithm.

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Notes

  1. http://archive.ics.uci.edu/ml/datasets.html.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (No. 10771213) and Chinese Universities Scientific Found (No. 2010JS043). The authors gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation.

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Authors and Affiliations

  1. College of science, China Agricultural University, Mailbox 71, No. 17 Qinghua East Road, 100083, Haidian, Beijing, People’s Republic of China

    Yitian Xu, Laisheng Wang & Ping Zhong

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  1. Yitian Xu
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  2. Laisheng Wang
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  3. Ping Zhong
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Correspondence to Yitian Xu.

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Xu, Y., Wang, L. & Zhong, P. A rough margin-based ν-twin support vector machine. Neural Comput & Applic 21, 1307–1317 (2012). https://doi.org/10.1007/s00521-011-0565-y

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  • DOI: https://doi.org/10.1007/s00521-011-0565-y

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