Towards an expert system for enantioseparations: induction of rules using machine learning

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Bryant, CH, Adam, AE, Taylor, DR and Rowe, RC 1996, 'Towards an expert system for enantioseparations: induction of rules using machine learning' , Chemometrics and Intelligent Laboratory Systems, 34 (1) , pp. 21-40.

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Official URL: http://dx.doi.org/10.1016/0169-7439(96)00016-0

Abstract

A commercially available machine induction tool was used in an attempt to automate the acquisition of the knowledge needed for an expert system for enantioseparations by High Performance Liquid Chromatography using Pirkle-type chiral stationary phases (CSPs). Various rule-sets were induced that recommended particular CSP chiral selectors based on the structural features of an enantiomer pair. The results suggest that the accuracy of the optimal rule-set is 63% + or - 3% which is more than ten times greater than the accuracy that would have resulted from a random choice.

Item Type:	Article
Uncontrolled Keywords:	expert systems, enantioseparations, machine learning
Themes:	Subjects / Themes > Q Science > QA Mathematics > QA075 Electronic computers. Computer science Subjects / Themes > Q Science > QD Chemistry Subjects outside of the University Themes
Schools:	Colleges and Schools > College of Science & Technology Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > Data Mining and Pattern Recognition Research Centre
Journal or Publication Title:	Chemometrics and Intelligent Laboratory Systems
Publisher:	Elsevier
Refereed:	Yes
ISSN:	01697439
Related URLs:	Author
Depositing User:	Dr Chris H. Bryant
Date Deposited:	17 Feb 2009 15:25
Last Modified:	27 Sep 2011 12:32
URI:	http://usir.salford.ac.uk/id/eprint/1772

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