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Volumn 2, Issue , 2004, Pages 1327-1330

Feature weighting using neural networks

Author keywords

[No Author keywords available]

Indexed keywords

DATASETS; DECISION TREES; FEATURE SELECTION; FEATURE WEIGHTING;

EID: 10944238700     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2004.1380137     Document Type: Conference Paper
Times cited : (17)

References (10)
  • 4
    • 0026156490 scopus 로고
    • A nearest hyper-rectangle learning method
    • S. L. Salzberg, "A nearest hyper-rectangle learning method," Machine Learning, vol. 6, pp. 251-276, 1991.
    • (1991) Machine Learning , vol.6 , pp. 251-276
    • Salzberg, S.L.1
  • 5
    • 0000217085 scopus 로고
    • Tolerating noisy, irrelevant, and novel attributes in instance-based learning algorithms
    • D. W. Aha, "Tolerating noisy, irrelevant, and novel attributes in instance-based learning algorithms," International Journal of Man-Machine Studies, vol. 36, pp. 267-287, 1992.
    • (1992) International Journal of Man-machine Studies , vol.36 , pp. 267-287
    • Aha, D.W.1
  • 7
    • 0031073477 scopus 로고    scopus 로고
    • A review and empirical evaluation of feature weighting methods for a class of lazy learning algorithms
    • D. Wettschereck, D. W. Aha, and T. Mohri, "A review and empirical evaluation of feature weighting methods for a class of lazy learning algorithms," Artificial Intelligence Review, vol. 11, pp. 273-314, 1997.
    • (1997) Artificial Intelligence Review , vol.11 , pp. 273-314
    • Wettschereck, D.1    Aha, D.W.2    Mohri, T.3
  • 8
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximator
    • K. Hornik, M. Stinchcombe and H. White, "Multilayer feedforward networks are universal approximator," Neural Networks, vol. 2, pp. 359-366, 1989.
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.