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Volumn 5, Issue 1, 2001, Pages 31-36

An Innovative Way to Measure the Quality of a Neural Network Without the Use of a Test Set

Author keywords

Generalization capability; Neural networks; Quality factors

Indexed keywords

COMPUTATIONAL COSTS; GENERALIZATION CAPABILITY; NEURAL UNITS; NEURAL-NETWORKS; OUTPUT FUNCTIONS; PRODUCTION PHASE; QUALITY FACTORS; TEST SETS; TRAINING PATTERNS; TRAINING SETS;

EID: 13844262008     PISSN: 13430130     EISSN: 18838014     Source Type: Journal    
DOI: 10.20965/jaciii.2001.p0031     Document Type: Article
Times cited : (10)

References (16)
  • 1
    • 0000155950 scopus 로고
    • The cascadccorrelalion learning architecture, advances in neural information processing systems
    • D.S.Touretzky ed
    • S. E. Fahlman and C. Lebiere. "The cascadccorrelalion learning architecture, advances in neural information processing systems." Advances in Neural Information Processing Systems. D.S.Touretzky ed., 2:524-532, 1990.
    • (1990) Advances in Neural Information Processing Systems , vol.2 , pp. 524-532
    • Fahlman, S. E.1    Lebiere, C.2
  • 2
    • 0003764428 scopus 로고
    • Technical Report, laboratory for Computational Statistics. Dept. of Statistics. Stanford University, Nov
    • J. Friedman. "Multivariate adaptive regression splines." Technical Report, laboratory for Computational Statistics. Dept. of Statistics. Stanford University, (102). Nov 1988.
    • (1988) Multivariate adaptive regression splines , Issue.102
    • Friedman, J.1
  • 5
    • 0030143634 scopus 로고    scopus 로고
    • On the behavior of artificial neural network classifiers in highdimensional spaces
    • 19
    • Y. Hamamoto. S. Uchimura and S. Tomita. "On the behavior of artificial neural network classifiers in highdimensional spaces." IEEE Trans on PAMI. 18(5):571 -574. 19%.
    • IEEE Trans on PAMI , vol.18 , Issue.5 , pp. 571-574
    • Hamamoto, Y.1    Uchimura, S.2    Tomita, S.3
  • 6
    • 85168765679 scopus 로고    scopus 로고
    • http://www.cs.utoronto.ca/-delve.
  • 9
    • 0028496580 scopus 로고
    • Weight smoothing to improve network generalization
    • S. N. J. Jack and J. Wang. "Weight smoothing to improve network generalization." IEEE Trans, on Neural Networks. 5(5):752-763, 1994.
    • (1994) IEEE Trans, on Neural Networks , vol.5 , Issue.5 , pp. 752-763
    • Jack, S. N. J.1    Wang, J.2
  • 10
    • 0026382928 scopus 로고
    • Encoding a priori information in feedforward networks
    • W. H. Joerding and J. L. Meador. "Encoding a priori information in feedforward networks." Neural Networks. 4(6):847-856. 1991.
    • (1991) Neural Networks , vol.4 , Issue.6 , pp. 847-856
    • Joerding, W. H.1    Meador, J. L.2
  • 11
    • 0027268953 scopus 로고
    • Parity with two layered feedforward nets
    • J. M. Minor. "Parity with two layered feedforward nets." Neural Networks, 6(5):705-707, 1993.
    • (1993) Neural Networks , vol.6 , Issue.5 , pp. 705-707
    • Minor, J. M.1
  • 13
    • 33846446220 scopus 로고    scopus 로고
    • Restart procedures for the conjugate gradient method
    • ll)77
    • M. J. D. Powell. "Restart procedures for the conjugate gradient method." Mathematical Programming, 12:241-254. ll)77
    • Mathematical Programming , vol.12 , pp. 241-254
    • Powell, M. J. D.1
  • 14
    • 0029306953 scopus 로고
    • Similarities of error rcgularization. sigmoid gain scaling, target smoothing, and training with jitter
    • R. Russell. J. Robert. I. Marks and O. Seho. "Similarities of error rcgularization. sigmoid gain scaling, target smoothing, and training with jitter." IEEE Trans, on Neural Networks. 6(3):529-538, 1995.
    • (1995) IEEE Trans, on Neural Networks , vol.6 , Issue.3 , pp. 529-538
    • Russell, R.1    Robert, J.2    Marks, I.3    Seho, O.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.