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KERNEL: a system for Knowledge Extraction and Refinement by NEural Learning

By Giovanna Castellano, Ciro Castiello and Anna Maria Fanelli


This paper presents KERNEL, a neuro-fuzzy system for the extraction of knowledge directly from data. The KERNEL system conforms to the KBN approach which concerns the use and representation of explicit knowledge within the neurocomputing paradigm. A specific neural network is designed, that reflects in its topology the structure of the fuzzy inference model on which is based the KERNEL system. For the implementation of the system, a toolbox developed in the Matlab environment is proposed. A well-known classification benchmark is used as illustrative example

Year: 2002
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