Introduction to probability and statistics (7th ed.)
Introduction to probability and statistics (7th ed.)
Neural-Network-Based Fuzzy Logic Control and Decision System
IEEE Transactions on Computers - Special issue on artificial neural networks
C4.5: programs for machine learning
C4.5: programs for machine learning
Extracting Refined Rules from Knowledge-Based Neural Networks
Machine Learning
Knowledge-based artificial neural networks
Artificial Intelligence
Structural adaptation and generalization in supervised feed-forward networks
Journal of Artificial Neural Networks
Extraction of rules from discrete-time recurrent neural networks
Neural Networks
Symbolic Representation of Neural Networks
Computer - Special issue: neural computing: companion issue to Spring 1996 IEEE Computational Science & Engineering
Machine learning and image interpretation
Machine learning and image interpretation
A hybrid intelligent architecture and revising domain knowledge
A hybrid intelligent architecture and revising domain knowledge
Neural Networks in Computer Intelligence
Neural Networks in Computer Intelligence
Logic Minimization Algorithms for VLSI Synthesis
Logic Minimization Algorithms for VLSI Synthesis
Chi2: Feature Selection and Discretization of Numeric Attributes
TAI '95 Proceedings of the Seventh International Conference on Tools with Artificial Intelligence
Concept acquisition through representational adjustment
Concept acquisition through representational adjustment
Theory refinement of bayesian networks with hidden variables
Theory refinement of bayesian networks with hidden variables
Understanding neural networks via rule extraction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
IEEE Transactions on Neural Networks
Understanding the Crucial Role of AttributeInteraction in Data Mining
Artificial Intelligence Review
Binary Rule Generation via Hamming Clustering
IEEE Transactions on Knowledge and Data Engineering
Rough-Fuzzy MLP: Modular Evolution, Rule Generation, and Evaluation
IEEE Transactions on Knowledge and Data Engineering
Instance-Based Method to Extract Rules from Neural Networks
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
A Knowledge Discovery by Fuzzy Rule Based Hopfield Network
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Determining Hyper-planes to Generate Symbolic Rules
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Rule Reduction over Numerical Attributes in Decision Tree Using Multilayer Perceptron
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Computationally Efficient Heuristics for If-Then Rule Extraction from Freed-Forward Neural Networks
DS '00 Proceedings of the Third International Conference on Discovery Science
Rule extraction: using neural networks or for neural networks?
Journal of Computer Science and Technology
Credit rating analysis with support vector machines and neural networks: a market comparative study
Decision Support Systems - Special issue: Data mining for financial decision making
A New Complicated-Knowledge Representation Approach Based on Knowledge Meshes
IEEE Transactions on Knowledge and Data Engineering
Extracting linguistic quantitative rules from supervised neural networks
International Journal of Knowledge-based and Intelligent Engineering Systems
Extraction of fuzzy rules from support vector machines
Fuzzy Sets and Systems
Artificial Intelligence in Medicine
Short communication: Specificity rule discovery in HIV-1 protease cleavage site analysis
Computational Biology and Chemistry
Short communication: Specificity rule discovery in HIV-1 protease cleavage site analysis
Computational Biology and Chemistry
A novel Supervised Instance Selection algorithm
International Journal of Business Intelligence and Data Mining
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Interpretable Piecewise Linear Classifier
Neural Information Processing
Knowledge-internalization process for neural-networks practitioners
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Improving rule extraction from neural networks by modifying hidden layer representations
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Necessary first-person axioms of neuroconsciousness
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Inversion of a neural network via interval arithmetic for rule extraction
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Review: Hybrid expert systems: A survey of current approaches and applications
Expert Systems with Applications: An International Journal
Designing a decompositional rule extraction algorithm for neural networks
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
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
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
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
Fault fuzzy rule extraction from AC motors by neuro-fuzzy models
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Predictability of rules in HIV-1 protease cleavage site analysis
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
A model for single and multiple knowledge based networks
Artificial Intelligence in Medicine
Reinforcement learning for rule extraction from a labeled dataset
Cognitive Systems Research
Recurrent networks for structured data - A unifying approach and its properties
Cognitive Systems Research
Artificial Intelligence in Medicine
White box radial basis function classifiers with component selection for clinical prediction models
Artificial Intelligence in Medicine
An Abductive-Reasoning Guide for Finance Practitioners
Computational Economics
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Hybrid Intelligent Systems that combine knowledge-based and artificial neural network systems typically have four phases involving domain knowledge representation, mapping of this knowledge into an initial connectionist architecture, network training, and rule extraction, respectively. The final phase is important because it can provide a trained connectionist architecture with explanation power and validate its output decisions. Moreover, it can be used to refine and maintain the initial knowledge acquired from domain experts. In this paper, we present three rule-extraction techniques. The first technique extracts a set of binary rules from any type of neural network. The other two techniques are specific to feedforward networks, with a single hidden layer of sigmoidal units. Technique 2 extracts partial rules that represent the most important embedded knowledge with an adjustable level of detail, while the third technique provides a more comprehensive and universal approach. A rule-evaluation technique, which orders extracted rules based on three performance measures, is then proposed. The three techniques area applied to the iris and breast cancer data sets. The extracted rules are evaluated qualitatively and quantitatively, and are compared with those obtained by other approaches.