@article {10.3844/jmssp.2013.208.218,
article_type = {journal},
title = {A NOVEL MULTICLASS SUPPORT VECTOR MACHINE ALGORITHM USING MEAN REVERSION AND COEFFICIENT OF VARIANCE},
author = {Premanode, Bhusana and Vongprasert, Jumlong and Sopipan, Nop and Toumazou, Christofer},
volume = {9},
year = {2013},
month = {Jul},
pages = {208-218},
doi = {10.3844/jmssp.2013.208.218},
url = {https://thescipub.com/abstract/jmssp.2013.208.218},
abstract = {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.},
journal = {Journal of Mathematics and Statistics},
publisher = {Science Publications}
}