A new support vector machine model for outlier detection

Yimin Ai; Jun Xing

doi:10.1117/12.2010611

14 March 2013 A new support vector machine model for outlier detection

Yimin Ai, Jun Xing

Proceedings Volume 8768, International Conference on Graphic and Image Processing (ICGIP 2012); 87680E (2013) https://doi.org/10.1117/12.2010611
Event: 2012 International Conference on Graphic and Image Processing, 2012, Singapore, Singapore

Abstract

Outlier detection has attracted more and more attentions from researchers due to its extensive applications in various fields. In this paper, a new SVM (Support Vector Machine) model is presented for a special type of outlier detection problem, where the majority of training data is normal sample and it also contains a small number of anomaly samples. The experimental results on several datasets show that the proposed algorithm is valid and can achieve better accuracy compared with the published algorithms.

Citation Download Citation

Yimin Ai and Jun Xing "A new support vector machine model for outlier detection", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87680E (14 March 2013); https://doi.org/10.1117/12.2010611

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