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Design of Nearest Prototype Classifier by using Differential Evolutionary Algorithm

차분진화 알고리즘을 이용한 Nearest Prototype Classifier 설계

  • 노석범 (원광대학교 전자 및 제어 공학부) ;
  • 안태천 (원광대학교 부설 공업기술개발연구소)
  • Received : 2011.05.22
  • Accepted : 2011.08.16
  • Published : 2011.08.25

Abstract

In this paper, we proposed a new design methodology to improve the classification performance of the Nearest Prototype Classifier which is one of the simplest classification algorithm. To optimize the position vectors of the prototypes in the nearest prototype classifier, we use the differential evolutionary algorithm. The optimized position vectors of the prototypes result in the improvement of the classification performance. The new method to determine the class labels of the prototypes, which are defined by the differential evolutionary algorithm, is proposed. In addition, the experimental application covers a comparative analysis including several previously commonly encountered methods.

본 논문에서는 가장 단순한 구조를 가진 Nearest Prototype Classifier의 성능 개선을 위해 차분 진화 알고리즘을 적용하여 prototype의 위치를 결정하는 방법을 제안하였다. 차분 진화 알고리즘을 이용하여 prototype의 위치 벡터가 결정이 되며, 차분 진화 알고리즘에 의해 결정된 prototype의 class label을 결정하기 위한 class label 결정 알고리즘도 제안하였다. 제안된 알고리즘의 성능 평가를 위해 기존의 패턴 분류기와 비교 결과를 보인다.

Keywords

References

  1. A.K. Jain, P. W. Duin, J. Mao, "Statistical pattern recognition: a review," IEEE trans. pattern Anal. Mach. Intell. vol. 22, no. 1, pp. 4-37, 2000. https://doi.org/10.1109/34.824819
  2. C. L. Liu, H. Sako, "Class-specific feature polynomial classifier for pattern classification and its application to hand written numeral recognition," Pattern recognition, vol. 39, pp. 669-681, 2006. https://doi.org/10.1016/j.patcog.2005.04.021
  3. U. Krebel, J. Schurmann, "Pattern classification techniques based on function approximation," Handbook of character recognition and document image analysis, World Scientific, Singapore, pp. 49-78, 1997.
  4. J Shurmann, Pattern classification: a unified view of statistical and neural approaches, Wiley Interscience, New York, 1996.
  5. F. Fernandez, R. Isasi, "Evolutionary Design of Nearest Prototype Classifiers," Journal of Heuristics, vol. 10, pp. 431-454, 2004. https://doi.org/10.1023/B:HEUR.0000034715.70386.5b
  6. W. Lam, C. K. Keung, C. X. Ling, "Learning good prototypes for classification using filtering and abstraction of instances," Pattern Recognition, vol. 35, pp. 1491-1506, 2002. https://doi.org/10.1016/S0031-3203(01)00131-5
  7. J. C. Bezdek, L. I. Kuncheva, "Nearest Neighbor classifier designs: An Experimental Study," International Journal of Intelligent Systems, vol. 16, pp. 1445-1473, 2001. https://doi.org/10.1002/int.1068
  8. Ludmila I. Kuncheva, James C. Bezdek, "A Fuzzy Generalized Nearest Prototype Classifier," IFSA 97 Prague Proceedings III, pp. 217-222, 1997.
  9. Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, Berlin Heidelberg, 1996.
  10. 황희수, "적응성 있는 차분 진화에 의한 함수최적화와 이벤트 클러스터링," 한국 지능시스템학회 논문지, 제12권, 5호, pp. 451-461, 2002. https://doi.org/10.5391/JKIIS.2002.12.5.451
  11. 조세희, 정대형, 오성권, "차분진화 알고리즘을 이용한 FCM 기반 퍼지시스템의 최적설계에 관한 연구," 한국지능시스템학회 2011년도 춘계학술대회 학술발표논문집, 제21권, 1호, pp. 131-132, 2011.
  12. L. I. Kuncheva, J. C. Bezdek, "Nearest Prototype Classification: Clustering, Genetic Algorithm, or Random Search?," IEEE Trans. On Systems, Man, and Cybernectics-Part C, vol. 28, no. 1, pp. 160-164, 1998. https://doi.org/10.1109/5326.661099
  13. R. Storn, K. V. Price, "Differential Evolution-a fast and efficient heuristic for global optimization over continuous spaces," Journal of Global Optimization, vol. 11, pp. 341-359, 1997. https://doi.org/10.1023/A:1008202821328
  14. A. Cervantes, I. M. Galvan, P. Isasi, "AMPSO: A New Particle Swarm Method for Nearest Neighborhood Classification," IEEE Trans. On Systems, Man, and Cybernectics-Part B, vol. 39, no. 5, pp. 1082-1091, 2009. https://doi.org/10.1109/TSMCB.2008.2011816