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Fuzzy Semi-supervised Large Margin One-Class Support Vector Machine

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Some Current Advanced Researches on Information and Computer Science in Vietnam (NAFOSTED 2014)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 341))

Abstract

One-class Support Vector Machine (OCSVM) is one of state-of-the-art kernel-based methods for one-class classification problem. OCSVM produces the good performance for imbalanced dataset. Nonetheless, it cannot make use of negative data samples and also cannot utilize unlabeled data to boost the classifier. In this paper, we first extend the model of OCSVM to make use of the information carried by negative data samples for classification and then propose how to integrate the semi-supervised paradigm to the extended OCSVM for utilizing the unlabeled data to increase the classifier’s generalization ability. Finally, we show how to apply the fuzzy theory to the proposed semi-supervised one-class classification method for efficiently handling noises and outliers.

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Author information

Authors and Affiliations

  1. Faculty of Information Technology, HCMc University of Pedagogy, 280 An Duong Vuong St., Ho Chi Minh City, Vietnam

    Trung Le, Van Nguyen, Thien Pham & Mi Dinh

  2. Faculty of Information Technology, HCMc University of Science, 227 Nguyen Van Cu St., Ho Chi Minh City, Vietnam

    Thai Hoang Le

Authors
  1. Trung Le
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  2. Van Nguyen
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  3. Thien Pham
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  4. Mi Dinh
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  5. Thai Hoang Le
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Corresponding author

Correspondence to Trung Le .

Editor information

Editors and Affiliations

  1. Institute of Information Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam

    Quang A. Dang

  2. IT Research and Development Center, Hanoi University, Hanoi, Vietnam

    Xuan Hoai Nguyen

  3. Faculty of Information Technology, University of Science, Hochiminh, Vietnam

    Hoai Bac Le

  4. University of Engineering and Technology, Hanoi, Vietnam

    Viet Ha Nguyen

  5. Posts and Telecommunications Institute of Technology, Ho Chi Minh, Vietnam

    Vo Nguyen Quoc Bao

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Le, T., Nguyen, V., Pham, T., Dinh, M., Le, T.H. (2015). Fuzzy Semi-supervised Large Margin One-Class Support Vector Machine. In: Dang, Q., Nguyen, X., Le, H., Nguyen, V., Bao, V. (eds) Some Current Advanced Researches on Information and Computer Science in Vietnam. NAFOSTED 2014. Advances in Intelligent Systems and Computing, vol 341. Springer, Cham. https://doi.org/10.1007/978-3-319-14633-1_5

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  • DOI: https://doi.org/10.1007/978-3-319-14633-1_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14632-4

  • Online ISBN: 978-3-319-14633-1

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