The KIPS Transactions:PartB (정보처리학회논문지B)

Korea Information Processing Society (한국정보처리학회)
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An Integrated Method for Generating Inductive Rule Sets

결합적 방법에 의한 귀납법칙 집합의 생성

  • Published : 2003.02.01
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Abstract

The rule induction system generates a set of inductive rules, and the task of selecting an optimal rule subset is one of the important problem in the area of rule induction. This paper proposes a new learning method which combines rule induction system with the paradigm of genetic algorithm. This paper shows that genetic algorithm can be effectively applied to optimal rule selection problem. The proposed system was evaluated using a set of different machine learning data sets and, showed better performance in all cases than other traditional methods.

귀납법칙 생성 시스템은 데이터에서부터 법칙을 자동으로 발견하는 시스템으로서 현재 많은 연구가 진행되고 있다. 본 논문은 정보이론을 이용하여 데이터로부터 귀납법칙을 자동으로 생성하는 시스템을 제시하고 또한 귀납법칙 생성 시스템에 의하여 생성되는 규칙들 중에서 가장 좋은 성능을 보이는 규칙 집합을 구하기 위하여 이를 유전자 알고리즘과 결합시켜 최적화된 귀납법칙 집합을 탐색하는 방법을 제시하였다. 제안된 시스템의 성능을 평가하기 위하여 다수의 기계학습 데이터를 사용하여 기존의 다른 방법들과 비교하였으며, 제안된 시스템은 대부분의 경우에 좋은 정확도를 제공하였다.

Keywords

References

  1. Cendrowska, J., 'PRISM : An Algorithms for Inducing Modular Rules,' Int. J. of Man-Machine Studies, Vol.27 pp.349- 379, 1987 https://doi.org/10.1016/S0020-7373(87)80003-2
  2. Clark, P. and T. Niblett, 'The CN2 Induction Algorithms,' Machine Learning, Vol.3, pp.261-283, 1989 https://doi.org/10.1023/A:1022641700528
  3. Bloedorn, E. and R. S. Michalski, 'Data-driven Construc?tive Induction in AQ17-DCI : A Method and Experiments,' Reports of Machine Learning and Inference Laboratory, Center for Artificial Intelligence, George Mason University, 1991
  4. De Jong, K. A., Spears, W. H. and Golden, D. F., 'Using Genetic Algorithms for Concept Learning,' Machine Learning, Vol.13, pp.161-188, 1993 https://doi.org/10.1023/A:1022617912649
  5. Quinlan, J. R., 'C4.5 : Programs for Machine Learning,' San Mateo, CA : Morgan kaufmann, 1993
  6. Jerzy, W. Bala and Kenneth, A. De Jong and Peter, W. Pachowicz, 'Multi strategy Learning from Engineering Data by Integrating Inductive Generalization and Genetic Algorithms,' Machine Learning, Vol.4, pp.417-487, 1994
  7. Beran, R. J., 'Minimum Hellinger Distance for Parametric Models,' Ann. Statics, Vol.5, pp.445-463, 1977 https://doi.org/10.1214/aos/1176343842
  8. Ryszard S. Michalski, 'Inferential Theory of Learning,' Machine Learning, Vol.4, pp.3-61, 1994
  9. De Jong, K. 'Learning with Genetic Algorithms : An Overview,' in Machine Learning, Vol.3, No.3, pp.123-138, 1988 https://doi.org/10.1007/BF00113894
  10. Haleh Vafaie and Kenneth De Jong 'Improving a Rule Induction System using Genetic Algorithms,' Machine Learning, Vol.4, pp.453-469, 1994
  11. DeJong, K. A. Spears, W. M. and Gordon, D. F. 'Using Genetic Algorithms for Concepts learning,' Machine Learning, pp.161-188, 1993 https://doi.org/10.1023/A:1022617912649
  12. Booker, L. B., Goldberg, D. E. and Holland, J. H. 'Classifier Systems and Genetic Algorithms,' Artificial Intelligence, pp.235-282, 1989 https://doi.org/10.1016/0004-3702(89)90050-7