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Volumn 3, Issue 5, 1990, Pages 535-549

Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappings

Author keywords

Convergence; Feedforward networks; Learning; Nonparametric; Regression

Indexed keywords

LEARNING SYSTEMS;

EID: 0025635525     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/0893-6080(90)90004-5     Document Type: Article
Times cited : (455)

References (35)
  • 2
    • 0024931167 scopus 로고
    • A new approach for finding the global minimum of error function of neural networks
    • (1989) Neural Networks , vol.2 , pp. 367-374
    • Baba1
  • 9
    • 0024866495 scopus 로고
    • On the approximate realization of continuous mappings by neural networks
    • (1989) Neural Networks , vol.2 , pp. 183-192
    • Funahashi1
  • 19
    • 0001462696 scopus 로고
    • L, cross-validation and generalized cross validation: Discrete index set
    • (1987) The Annals of Statistics , vol.15 , pp. 958-975
    • Li1
  • 33
  • 34
    • 84910776197 scopus 로고
    • A practical cross-validation method for multilayer feedforward networks
    • (1989) Appl Nurs Res
    • White1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.