C4.5: programs for machine learning
C4.5: programs for machine learning
Self-organizing maps
Foundations of Neuro-Fuzzy Systems
Foundations of Neuro-Fuzzy Systems
IEEE Transactions on Neural Networks
A new methodology of extraction, optimization and application of crisp and fuzzy logical rules
IEEE Transactions on Neural Networks
On the Generalization Ability of GRLVQ Networks
Neural Processing Letters
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Knowledge extraction from unsupervised multi-topographic neural network models
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Perspectives of self-adapted self-organizing clustering in organic computing
BioADIT'06 Proceedings of the Second international conference on Biologically Inspired Approaches to Advanced Information Technology
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Generalized relevance learning vector quantization (GRLVQ) [4] constitutes a prototype based clustering algorithm based on LVQ [5] with energy function and adaptive metric. We propose a method for extracting logical rules from a trained GRLVQ-network. Real valued attributes are automatically transformed to symbolic values. The rules are given in the form of a decision tree yielding several advantages: hybrid symbolic/subsymbolic descriptions can be obtained as an alternative and the complexity of the rules can be controlled.