메뉴 건너뛰기




Volumn 2, Issue , 2006, Pages 1561-1568

Bounding XCS's parameters for unbalanced datasets

Author keywords

Class Imbalance; Evolutionary Computation; Genetic Algorithms; Learning Classifier Systems; Machine Learning

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATABASE SYSTEMS; GENETIC ALGORITHMS; PARAMETER ESTIMATION; PROBABILITY;

EID: 33750245167     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1143997.1144250     Document Type: Conference Paper
Times cited : (35)

References (12)
  • 1
    • 0043284115 scopus 로고    scopus 로고
    • Accuracy-based learning classifier systems: Models, analysis and applications to classification tasks
    • Bernadó-Mansilla, E. and Garrell, J.M. Accuracy-Based Learning Classifier Systems: Models, Analysis and Applications to Classification Tasks. Evolutionary Computation, 11(3):209-238, 2003.
    • (2003) Evolutionary Computation , vol.11 , Issue.3 , pp. 209-238
    • Bernadó-Mansilla, E.1    Garrell, J.M.2
  • 2
    • 0041780883 scopus 로고    scopus 로고
    • Analysis and improvement of fitness exploration in XCS: Bounding models, tournament selection, and bilateral accuracy
    • Butz, M.V., Goldberg, D., and Tharankunnel, K. Analysis and improvement of fitness exploration in XCS: bounding models, tournament selection, and bilateral accuracy. Evolutionary Computation, 11(3):239-277, 2003.
    • (2003) Evolutionary Computation , vol.11 , Issue.3 , pp. 239-277
    • Butz, M.V.1    Goldberg, D.2    Tharankunnel, K.3
  • 4
    • 84942854203 scopus 로고    scopus 로고
    • An algorithmic description of XCS
    • P. Lanzi, W. Stolzmann, and S. Wilson, editors, Advances in Learning Classifier Systems: Proceedings of the Third International Workshop. Springer
    • Butz, M.V. and Wilson, S.W. An algorithmic description of XCS. In P. Lanzi, W. Stolzmann, and S. Wilson, editors, Advances in Learning Classifier Systems: Proceedings of the Third International Workshop, volume 1996 of Lecture Notes in Artificial Intelligence, pages 253-272. Springer, 2001.
    • (2001) Lecture Notes in Artificial Intelligence , vol.1996 , pp. 253-272
    • Butz, M.V.1    Wilson, S.W.2
  • 5
    • 27144528137 scopus 로고    scopus 로고
    • Differential negative reinforcement improves classifier system learning rate in two-class problems with unequal base rates
    • Morgan Kaufmann
    • Holmes, J.H. Differential negative reinforcement improves classifier system learning rate in two-class problems with unequal base rates. In Genetic Programming 1998: Proceedings of the Third Annual Conference, pages 635-642. Morgan Kaufmann, 1998.
    • (1998) Genetic Programming 1998: Proceedings of the Third Annual Conference , pp. 635-642
    • Holmes, J.H.1
  • 7
    • 33845536164 scopus 로고    scopus 로고
    • The class imbalance Problem: A systematic study
    • November
    • Japkowicz, N. and Stephen, S. The Class Imbalance Problem: A Systematic Study. Intelligent Data Analisis, 6(5):429-450, November 2002.
    • (2002) Intelligent Data Analisis , vol.6 , Issue.5 , pp. 429-450
    • Japkowicz, N.1    Stephen, S.2
  • 9
    • 27144524459 scopus 로고    scopus 로고
    • The class imbalance problem in UCS classifier system: Fitness adaptation
    • Edinburgh, UK. IEEE
    • Orriols-Puig, A. and Bernadó-Mansilla, E. The Class Imbalance Problem in UCS Classifier System: Fitness Adaptation. In Congress on Evolutionary Computation, volume 1, pages 604-611, Edinburgh, UK. 2005. IEEE.
    • (2005) Congress on Evolutionary Computation , vol.1 , pp. 604-611
    • Orriols-Puig, A.1    Bernadó-Mansilla, E.2
  • 10
    • 0001387704 scopus 로고
    • Classifier fitness based on accuracy
    • Wilson, S.W. Classifier Fitness Based on Accuracy. Evolutionary Computation, 3(2):149-175, 1995.
    • (1995) Evolutionary Computation , vol.3 , Issue.2 , pp. 149-175
    • Wilson, S.W.1
  • 12
    • 33750275082 scopus 로고    scopus 로고
    • Personal Communication, July
    • Wilson, S.W. Personal Communication, July 2005.
    • (2005)
    • Wilson, S.W.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.