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Conference paper

Extraction of Comprehensible Logical Rules from Neural Networks. Application of TREPAN in Bio and Chemoinformatics

Brian D. Hudson
David C. Whitley
Antony Browne
Martyn G. Ford


Full text: english pdf 152 Kb

page 557-561

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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.

Keywords

bioinformatics; chemoinformatics; neural networks; rule induction; decision trees

Hrčak ID:

2544

URI

https://hrcak.srce.hr/2544

Publication date:

20.12.2005.

Article data in other languages: croatian

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