Extraction of comprehensible logical rules from neural networks: application of TREPAN in bio and cheminformatics

Brian Hudson, David Whitley, A. Browne, M. Ford

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Abstract

TREPAN is an algorithm for the extraction of comprehensible rules from trained neural networks. The method has been applied successfully to biological sequence (bioinformatics) problems. It has now been extended to handle chemoinformatics (QSAR) datasets. The method has been shown to have advantages over traditional symbolic rule induction methods such as C5. Results obtained for bioinformatics and chemoinformatics problems using the TREPAN algorithm are presented.
Original languageEnglish
Pages (from-to)557-561
Number of pages5
JournalCroatica Chemica Acta
Volume78
Issue number4
Publication statusPublished - 2005

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