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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Online Support Vector Machine: A Survey
verfasst von : Xujun Zhou, Xianxia Zhang, Bing Wang
Erschienen in: Harmony Search Algorithm
Verlag: Springer Berlin Heidelberg
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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.