Rule Extraction from Neural Network by Genetic Algorithm with Pareto Optimization
作者： Urszula Markowska-Kaczmar , Paweł Wnuk-Lipiński
DOI: 10.1007/978-3-540-24844-6_66
关键词:
摘要: The method of rule extraction from a neural network based on the genetic approach with Pareto optimization is presented in paper. idea shortly described and details developed such as fitness function, operators structure chromosome are shown. was tested well known benchmark data sets. results these experiments discussed.
springer.com
sci-hub.se 参考文章(9)
Gerald W. Kimble, Information and Computer Science Information and Computer Science. pp. 180- 180 ,(1975)
Ashish Darbari, Rule Extraction from Trained ANN: A Survey s.n.. ,(2000)
Eckart Zitzler, Lothar Thiele, An evolutionary algorithm for multiobjective optimization: the strength Pareto approach TIK-Report. ,vol. 43, ,(1998) , 10.3929/ETHZ-A-004288833
R.T. Santos, J.C. Nievola, A.A. Freitas, Extracting comprehensible rules from neural networks via genetic algorithms 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks. Proceedings of the First IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (Cat. No.00. pp. 130- 139 ,(2000) , 10.1109/ECNN.2000.886228
C. L. Blake, UCI Repository of machine learning databases www.ics.uci.edu/〜mlearn/MLRepository.html. ,(1998)
Rudy Setiono, Extracting rules from pruned neural networks for breast cancer diagnosis Artificial Intelligence in Medicine. ,vol. 8, pp. 37- 51 ,(1996) , 10.1016/0933-3657(95)00019-4
I.A. Taha, J. Ghosh, Symbolic interpretation of artificial neural networks IEEE Transactions on Knowledge and Data Engineering. ,vol. 11, pp. 448- 463 ,(1999) , 10.1109/69.774103
C.L. Valenzuela, A simple evolutionary algorithm for multi-objective optimization (SEAMO) congress on evolutionary computation. ,vol. 1, pp. 717- 722 ,(2002) , 10.1109/CEC.2002.1007014
S. Mitra, Y. Hayashi, Neuro-fuzzy rule generation: survey in soft computing framework IEEE Transactions on Neural Networks. ,vol. 11, pp. 748- 768 ,(2000) , 10.1109/72.846746