research-article

Robust support vector machine with bullet hole image classification

Authors:

Qing Song,

Wenjie Hu,

Wenfang XieAuthors Info & Claims

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, Volume 32, Issue 4

Pages 440 - 448

https://doi.org/10.1109/TSMCC.2002.807277

Published: 01 November 2002 Publication History

Abstract

This paper proposes a robust support vector machine for pattern classification, which aims at solving the over-fitting problem when outliers exist in the training data set. During the robust training phase, the distance between each data point and the center of class is used to calculate the adaptive margin. The incorporation of the average techniques to the standard support vector machine (SVM) training makes the decision function less detoured by outliers, and controls the amount of regularization automatically. Experiments for the bullet hole classification problem show that the number of the support vectors is reduced, and the generalization performance is improved significantly compared to that of the standard SVM training.

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Xin RLiu HChen PZhao Z(2023)Robust and accurate performance anomaly detection and prediction for cloud applications: a novel ensemble learning-based frameworkJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-022-00383-612:1Online publication date: 14-Jan-2023
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Shrivastava SShukla SKhare N(2023)A stable variant of linex loss SVM for handling noise with reduced hyperparametersInformation Sciences: an International Journal10.1016/j.ins.2023.119402646:COnline publication date: 29-Aug-2023
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Index Terms

Robust support vector machine with bullet hole image classification
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
    2. Machine learning approaches
      1. Classification and regression trees

Index terms have been assigned to the content through auto-classification.

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cover image IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews Volume 32, Issue 4

November 2002

257 pages

ISSN:1094-6977

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IEEE Press

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Published: 01 November 2002

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Shrivastava SShukla SKhare N(2024)Support vector machine with eagle loss functionExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.122168238:PEOnline publication date: 27-Feb-2024
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Xin RLiu HChen PZhao Z(2023)Robust and accurate performance anomaly detection and prediction for cloud applications: a novel ensemble learning-based frameworkJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-022-00383-612:1Online publication date: 14-Jan-2023
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