TY  - JOUR
AU  - Premanode, Bhusana 
AU  - Vongprasert, Jumlong 
AU  - Sopipan, Nop 
AU  - Toumazou, Christofer 
PY  - 2013
TI  - A NOVEL MULTICLASS SUPPORT VECTOR MACHINE ALGORITHM USING MEAN REVERSION AND COEFFICIENT OF VARIANCE
JF  - Journal of Mathematics and Statistics
VL  - 9
IS  - 3
DO  - 10.3844/jmssp.2013.208.218
UR  - https://thescipub.com/abstract/jmssp.2013.208.218
AB  - Inaccuracy of a kernel function used in Support Vector Machine (SVM) can be found when simulated with nonlinear and stationary datasets. To minimise the error, we propose a new multiclass SVM model using mean reversion and coefficient of variance algorithm to partition and classify imbalance in datasets. By introducing a series of test statistic, simulations of the proposed algorithm outperformed the performance of the SVM model without using multiclass SVM model.