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Volumn , Issue , 2003, Pages 99-113

Techniques for extracting classification and regression rules from artificial neural networks

Author keywords

Accuracy; Artificial neural networks; Classification algorithms; Feedforward neural networks; Prediction algorithms; Sections; Training

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL METHODS; NEURAL NETWORKS; PERSONNEL TRAINING;

EID: 85006992050     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1109/9780470544297.ch7     Document Type: Chapter
Times cited : (10)

References (16)
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  • 3
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    • Extracting Rules from Artificial Neural Networks with Distributed Representation
    • S. Thrun. “Extracting Rules from Artificial Neural Networks with Distributed Representation.” Adv. NIPS, vol. 7, 1995.
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  • 4
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    • Symbolic Representation of Neural Networks
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    • Setiono, R.1    Liu, H.2
  • 6
    • 0342378106 scopus 로고    scopus 로고
    • NeuroLinear: From Neural Networks to Oblique Decision Rules
    • R. Setiono and H. Liu. “NeuroLinear: From Neural Networks to Oblique Decision Rules.” Neurocomputing, vol. 17, no. 1, 1-24, 1997.
    • (1997) Neurocomputing , vol.17 , Issue.1 , pp. 1-24
    • Setiono, R.1    Liu, H.2
  • 8
    • 0036565303 scopus 로고    scopus 로고
    • Extraction of Rules from Artificial Neural Networks for Nonlinear Regression
    • R. Setiono, W. K. Leow, and J. Zurada. “Extraction of Rules from Artificial Neural Networks for Nonlinear Regression.” IEEE Trans. Neural Networks, vol. 13, no. 1, 567-577, 2002.
    • (2002) IEEE Trans. Neural Networks , vol.13 , Issue.1 , pp. 567-577
    • Setiono, R.1    Leow, W.K.2    Zurada, J.3
  • 10
    • 0030633575 scopus 로고    scopus 로고
    • A Penalty Function Approach for Pruning Feedforward Neural Networks
    • R. Setiono. “A Penalty Function Approach for Pruning Feedforward Neural Networks.” Neural Comput., vol. 9, no. 1, 185-204, 1997.
    • (1997) Neural Comput. , vol.9 , Issue.1 , pp. 185-204
    • Setiono, R.1
  • 13
    • 84980104458 scopus 로고
    • Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy
    • E. L. Altman. “Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy.” Finance, vol. 23, no. 3, 589-609 (1968).
    • (1968) Finance , vol.23 , Issue.3 , pp. 589-609
    • Altman, E.L.1
  • 14
    • 0030167785 scopus 로고    scopus 로고
    • Simultaneous Design and Training of Ontogenic Neural Network Classifiers
    • J. P. Ignizio and J. R. Soltys. “Simultaneous Design and Training of Ontogenic Neural Network Classifiers.” Comput. Oper. Res., vol. 23, no. 6, 535-546 (1996).
    • (1996) Comput. Oper. Res. , vol.23 , Issue.6 , pp. 535-546
    • Ignizio, J.P.1    Soltys, J.R.2
  • 16
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    • Attributes of the Performance of Central Processing Units: A Relative Performance Prediction Model
    • P. Ein-Dor and J. Feldmesser, “Attributes of the Performance of Central Processing Units: A Relative Performance Prediction Model,” Commun. ACM, vol. 30, no. 4, 308-3177, 1987.
    • (1987) Commun. ACM , vol.30 , Issue.4 , pp. 308-3177
    • Ein-Dor, P.1    Feldmesser, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.