A Unified Approach to the Extraction of Rules from Artificial Neural Networks and Support Vector Machines

Author:

Guerreiro João,Trigueiros Duarte

Publisher

Springer Berlin Heidelberg

Reference17 articles.

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2. Shavlik, J.W., Mooney, R.J., Towell, G.G.: Symbolic and Neural Learning Algorithms: An Experimental Comparison. Machine Learning 6, 111–143 (1991)

3. Weiss, S.M., Kapouleas, I.: An Empirical Comparison of Pattern Recognition, Neural Nets, and Machine Learning Classification Methods. In: 11th International Joint Conference on Artificial Intelligence, vol. 1, pp. 781–787. Morgan Kaufmann, Michigan (1989)

4. Etchells, T.A., Lisboa, P.J.G.: Orthogonal Search-based Rule Extraction (OSRE) for Trained Neural Networks: A Practical and Efficient Approach. IEEE Transactions on Neural Networks 17, 374–384 (2006)

5. Andrews, R., Diederich, J., Tickle, A.B.: Survey and Critique of Techniques for Extracting Rules from Trained Artificial Neural Networks. Knowledge-Based Systems 8, 373–389 (1995)

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