doi: 10.18178/ijfcc.2019.8.2.541
Improvement the Imbalanced Data Classification with Restarting Genetic Algorithm for Support Vector Machine Algorithm
Keerachart Suksut
1,*
,
Nuntawut Kaoungku
2
,
Kittisak Kerdprasop
3
,
Nittaya Kerdprasop
4
- 1 Computer Engineering Department, Rajamangala University of Technology Isan
- 2 School of Computer Engineering, Suranaree University of Technology
- 3 School of Computer Engineering and Knowledge Engineering Research Unit, SUT
- 4 School of Computer Engineering and Data Engineering Research Unit, SUT
Abstract
The general datamining algorithm also classify the balanced dataset, when the data have imbalanced the predicted rate over minority class is still low. The random sampling techniques has been applying to solve the imbalanced data, but sometimes the random technique has selected the features is clearly different from both, when the unseen data (from minority class) has features look like the majority class, the classification model show miss classification because the model learning sample data does not complete. To improve the performance to classify the data, the genetic algorithm is applying to finding the optimal parameter, but sometimes the genetic algorithm cannot find the best set of parameters because the random initial population is not cover the best set of parameters, in this research proposed the techniques to guarantee the genetic algorithm can find the optimal parameter by using restarting technique to re-create the initial population when the new generation show powerful less than the old population. The results show that proposed technique can improve the performance to classify the minority class from imbalanced dataset more than the other techniques.
Keywords
- Imbalanced data classification
- optimization parameter
- genetic algorithm
- restarting genetic algorithm
How to Cite
Keerachart Suksut, Nuntawut Kaoungku, Kittisak Kerdprasop, and Nittaya Kerdprasop, "Improvement the Imbalanced Data Classification with Restarting Genetic Algorithm for Support Vector Machine Algorithm," International Journal of Future Computer and Communication, vol. 8, no. 2, pp. 63-67, 2019. https://doi.org/ 10.18178/ijfcc.2019.8.2.541
Copyright & License
Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).