Communications of the ACM
Extracting Refined Rules from Knowledge-Based Neural Networks
Machine Learning
Neural Networks in Computer Intelligence
Neural Networks in Computer Intelligence
Symbolic Interpretation of Artificial Neural Networks
IEEE Transactions on Knowledge and Data Engineering
Understanding neural networks via rule extraction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Short communication: Specificity rule discovery in HIV-1 protease cleavage site analysis
Computational Biology and Chemistry
Cleavage site analysis using rule extraction from neural networks
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Prediction rule generation of MHC class i binding peptides using ANN and GA
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Rule generation using NN and GA for SARS-CoV cleavage site prediction
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Predictability of rules in HIV-1 protease cleavage site analysis
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
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In this paper, we address computational complexity issues of decompositional approaches to if-then rule extraction from feed-forward neural networks. We also introduce a computationally effcient technique based on ordered-attributes. It reduces search space significantly and finds valid and general rules for single nodes in the networks. Empirical results are shown.