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Online Support Vector Machine: A Survey

  • Xujun Zhou
  • Xianxia Zhang
  • Bing Wang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 382)

Abstract

Support Vector Machine (SVM) is one of the fastest growing methods of machine learning due to its good generalization ability and good convergence performance; it has been successfully applied in various fields, such as text classification, statistics, pattern recognition, and image processing. However, for real-time data collection systems, the traditional SVM methods could not perform well. In particular, they cannot well cope with the increasing new samples. In this paper, we give a survey on online SVM. Firstly, the description of SVM is introduced, then the brief summary of online SVM is given, and finally the research and development of online SVM are presented.

Keywords

Support vector machine Machine learning Generalization ability Convergence 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Shanghai Key Laboratory of Power Station Automation Technology, College of Mechatronics Engineering and AutomationShanghai UniversityShanghaiChina

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