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Volumn 3982 LNCS, Issue , 2006, Pages 590-599

Data reduction for instance-based learning using entropy-based partitioning

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); COMPUTATION THEORY; LEARNING SYSTEMS; SENSITIVITY ANALYSIS;

EID: 33745913300     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11751595_63     Document Type: Conference Paper
Times cited : (22)

References (11)
  • 2
    • 56749116285 scopus 로고    scopus 로고
    • On the combination of evolutionary algorithms and strafitied strategies for training set selection in data mining
    • In Press, Correted Proof
    • Cano, J.R., Herrera, F., Lozano M.: On the combination of evolutionary algorithms and strafitied strategies for training set selection in data mining. Applied Soft Computing, In Press, Correted Proof, (2005)
    • (2005) Applied Soft Computing
    • Cano, J.R.1    Herrera, F.2    Lozano, M.3
  • 5
    • 0036643351 scopus 로고    scopus 로고
    • Learning good prototypes for classification using filtering and abstraction of instances
    • Lam, W., Keung, C.L., Ling C.X.: Learning good prototypes for classification using filtering and abstraction of instances. Pattern Recognition, Vol. 35. (2002) 1491-1506
    • (2002) Pattern Recognition , vol.35 , pp. 1491-1506
    • Lam, W.1    Keung, C.L.2    Ling, C.X.3
  • 6
    • 18144451785 scopus 로고    scopus 로고
    • High training set size reduction by space partitioning and prototype abstraction
    • Sanchez, J.S.: High training set size reduction by space partitioning and prototype abstraction. Pattern Recognition, Vol. 37. (2004) 1561-1564
    • (2004) Pattern Recognition , vol.37 , pp. 1561-1564
    • Sanchez, J.S.1
  • 8
    • 0343081513 scopus 로고    scopus 로고
    • Reduction Techniques for instance-based learning algorithms
    • Wilson, D.R., Martinez, T.R.: Reduction Techniques for instance-based learning algorithms. Mach. Learning. 38 (2000) 257-286
    • (2000) Mach. Learning. , vol.38 , pp. 257-286
    • Wilson, D.R.1    Martinez, T.R.2
  • 9
    • 0347763609 scopus 로고    scopus 로고
    • Using evolutionary algorithms as instance selection for data reduction in kdd: An experimental study
    • Cano, J.R, Herrera, F., Lozano, M.: Using evolutionary algorithms as instance selection for data reduction in kdd: an experimental study. IEEE Transactions on Evolutionary Computation. 7 (6) (2003) 561-575
    • (2003) IEEE Transactions on Evolutionary Computation , vol.7 , Issue.6 , pp. 561-575
    • Cano, J.R.1    Herrera, F.2    Lozano, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.