메뉴 건너뛰기




Volumn 33, Issue 2, 2003, Pages 324-331

Evolutionary learning of hierarchical decision rules

Author keywords

Decision rules; Decision trees; Evolutionary algorithms (EAs); Supervised learning

Indexed keywords

BINARY CODES; DATABASE SYSTEMS; EVOLUTIONARY ALGORITHMS; LEARNING SYSTEMS; NEURAL NETWORKS;

EID: 0037381452     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2002.805696     Document Type: Article
Times cited : (84)

References (32)
  • 3
    • 1442267080 scopus 로고
    • Learning decision lists
    • R. L. Rivest, "Learning decision lists," Machine Learning, vol. 1, no. 2, pp. 229-246, 1987.
    • (1987) Machine Learning , vol.1 , Issue.2 , pp. 229-246
    • Rivest, R.L.1
  • 4
    • 34249966007 scopus 로고
    • The cn2 induction algorithm
    • P. Clark and T. Niblett, "The cn2 induction algorithm," Mach. Learn., vol. 3, no. 4, pp. 261-283, 1989.
    • (1989) Mach. Learn. , vol.3 , Issue.4 , pp. 261-283
    • Clark, P.1    Niblett, T.2
  • 8
    • 0004273826 scopus 로고
    • Colorado State Univ., Ft. Coffins, CO, Tech. Rep. CS-93-103
    • D. Whitley, "A genetic algorithm tutorial," Colorado State Univ., Ft. Coffins, CO, Tech. Rep. CS-93-103, 1993.
    • (1993) A Genetic Algorithm Tutorial
    • Whitley, D.1
  • 9
    • 3142607310 scopus 로고    scopus 로고
    • Genetic algorithms
    • S. Forrest, "Genetic algorithms," ACM Comput. Surv., vol. 28, no. 1, pp. 77-80, 1996.
    • (1996) ACM Comput. Surv. , vol.28 , Issue.1 , pp. 77-80
    • Forrest, S.1
  • 11
    • 0027696338 scopus 로고
    • Using genetic algorithms for concept learning
    • K. A. DeJong, W. M. Spears, and D. F. Gordon, "Using genetic algorithms for concept learning," Mach. Learn., vol. 1, no. 13, pp. 161-188, 1993.
    • (1993) Mach. Learn. , vol.1 , Issue.13 , pp. 161-188
    • DeJong, K.A.1    Spears, W.M.2    Gordon, D.F.3
  • 12
    • 0027696178 scopus 로고
    • A knowledge-intensive genetic algorithm for supervised learning
    • C. Z. Janikow, "A knowledge-intensive genetic algorithm for supervised learning," Mach. Learn., vol. 1, no. 13, pp. 169-228, 1993.
    • (1993) Mach. Learn. , vol.1 , Issue.13 , pp. 169-228
    • Janikow, C.Z.1
  • 13
    • 0000724053 scopus 로고
    • SIA: A supervised inductive algorithm with genetic search for learning attributes based concepts
    • G. Venturini, "SIA: A supervised inductive algorithm with genetic search for learning attributes based concepts," in Proc. Eur. Conf. Machine Learning, 1993, pp. 281-296.
    • (1993) Proc. Eur. Conf. Machine Learning , pp. 281-296
    • Venturini, G.1
  • 14
    • 0002061517 scopus 로고    scopus 로고
    • Using evolutionary algorithms to induce oblique decision trees
    • Las Vegas, NV
    • E. Cantu-Paz and C. Kamath, "Using evolutionary algorithms to induce oblique decision trees," in Proc. Genetic Evolutionary Computation Conf., Las Vegas, NV, 2000, pp. 1053-1060.
    • (2000) Proc. Genetic Evolutionary Computation Conf. , pp. 1053-1060
    • Cantu-Paz, E.1    Kamath, C.2
  • 15
    • 0002364921 scopus 로고    scopus 로고
    • A hybrid decision tree/genetic algorithm for coping with the problem of small disjuncts in data mining
    • Las Vegas, NV
    • D. R. Carvalho and A. A. Freitas, "A hybrid decision tree/genetic algorithm for coping with the problem of small disjuncts in data mining," in Proc. Genetic Evolutionary Computation Conf., Las Vegas, NV, 2000, pp. 1061-1068.
    • (2000) Proc. Genetic Evolutionary Computation Conf. , pp. 1061-1068
    • Carvalho, D.R.1    Freitas, A.A.2
  • 16
    • 0035892566 scopus 로고    scopus 로고
    • An evolutionary approach to estimating software development projects
    • J. S. Aguilar-Ruiz, J. C. Riquelme, and M. Toro, "An evolutionary approach to estimating software development projects," Inf. Softw. Technol., vol. 14, no. 43, pp. 875-882, 2001.
    • (2001) Inf. Softw. Technol. , vol.14 , Issue.43 , pp. 875-882
    • Aguilar-Ruiz, J.S.1    Riquelme, J.C.2    Toro, M.3
  • 17
    • 0000308566 scopus 로고
    • Real-coded genetic algorithms and interval-schemata
    • San Mateo, CA: Morgan Kaufman
    • L. J. Eshelman and J. D. Schaffer, "Real-coded genetic algorithms and interval-schemata," in Foundations of Genetic Algorithms-2. San Mateo, CA: Morgan Kaufman, 1993, pp. 187-202.
    • (1993) Foundations of Genetic Algorithms-2 , pp. 187-202
    • Eshelman, L.J.1    Schaffer, J.D.2
  • 19
    • 0002089210 scopus 로고
    • A new interpretation of schema notation that overturns the binary encoding constraint
    • J. Antonisse, "A new interpretation of schema notation that overturns the binary encoding constraint," in Proc. 3rd Int. Conf. Genetic Algorithms, 1989, pp. 86-97.
    • (1989) Proc. 3rd Int. Conf. Genetic Algorithms , pp. 86-97
    • Antonisse, J.1
  • 21
    • 0001482168 scopus 로고    scopus 로고
    • General cardinality genetic algorithms
    • G. J. Koehler, S. Bhattacharyya, and M. D. Vose, "General cardinality genetic algorithms," Evol. Computation, vol. 5, no. 4, pp. 439-459, 1998.
    • (1998) Evol. Computation , vol.5 , Issue.4 , pp. 439-459
    • Koehler, G.J.1    Bhattacharyya, S.2    Vose, M.D.3
  • 22
    • 0032149491 scopus 로고    scopus 로고
    • The simple genetic algorithm and the walsh transform: Part I, Theory
    • M. D. Vose and A. H. Wright, "The simple genetic algorithm and the walsh transform: Part I, Theory," Evol. Computation, vol. 6, no. 3, pp. 253-273, 1998.
    • (1998) Evol. Computation , vol.6 , Issue.3 , pp. 253-273
    • Vose, M.D.1    Wright, A.H.2
  • 23
    • 0032152453 scopus 로고    scopus 로고
    • The simple genetic algorithm and the walsh transform: Part II, The inverse
    • _, "The simple genetic algorithm and the walsh transform: Part II, The inverse," Evol. Computation, vol. 6, no. 3, pp. 275-289, 1998.
    • (1998) Evol. Computation , vol.6 , Issue.3 , pp. 275-289
  • 24
    • 0002364637 scopus 로고    scopus 로고
    • Three geometric approaches for representing decision rules in a supervised learning system
    • UU., Orlando, FL
    • J. S. Aguilar-Ruiz, J. C. Riquelme, and M. Toro, "Three geometric approaches for representing decision rules in a supervised learning system," in Proc. Genetic Evolutionary Computation Conf., vol. EE.UU., Orlando, FL, 1999, p. 771.
    • (1999) Proc. Genetic Evolutionary Computation Conf. , vol.EE , pp. 771
    • Aguilar-Ruiz, J.S.1    Riquelme, J.C.2    Toro, M.3
  • 25
  • 26
    • 0027580356 scopus 로고
    • Very simple classification rules perform well on most commonly used datasets
    • R. C. Holte, "Very simple classification rules perform well on most commonly used datasets," Mach. Learn., vol. 11, pp. 63-91, 1993.
    • (1993) Mach. Learn. , vol.11 , pp. 63-91
    • Holte, R.C.1
  • 27
    • 0001403575 scopus 로고
    • Genetic algorithms for real parameter optimization
    • San Mateo, CA: Morgan Kaufman
    • A. H. Wright, "Genetic algorithms for real parameter optimization," in Foundations of Genetic Algorithms-1. San Mateo, CA: Morgan Kaufman, 1991, pp. 205-218.
    • (1991) Foundations of Genetic Algorithms-1 , pp. 205-218
    • Wright, A.H.1
  • 30
    • 0001899045 scopus 로고    scopus 로고
    • Improved heterogeneous distance functions
    • D. R. Wilson and T. R. Martinez, "Improved heterogeneous distance functions," J. Artif. Intell. Res., vol. 6, no. 1, pp. 1-34, 1997.
    • (1997) J. Artif. Intell. Res. , vol.6 , Issue.1 , pp. 1-34
    • Wilson, D.R.1    Martinez, T.R.2
  • 32
    • 0029678894 scopus 로고    scopus 로고
    • Improved use of continuous attributes in c4.5
    • J. R. Quinlan, "Improved use of continuous attributes in c4.5," J. Artif. Intell. Res., vol. 4, pp. 77-90, 1996.
    • (1996) J. Artif. Intell. Res. , vol.4 , pp. 77-90
    • Quinlan, J.R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.