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Publication Detail
Data fusion by intelligent classifier combination
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Publication Type:Journal article
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Publication Sub Type:Article
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Authors:Buxton BF, Langdon WB, Barrett SJ
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Publisher:The Institute of Measurement and Control
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Publication date:2001
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Place of publication:UK
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Pagination:229, 234
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Journal:Measurement and Control
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Volume:34
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Issue:8
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Country:UK
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Print ISSN:0020-2940
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Author URL:
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Notes:Awarded best paper prize by the Worshipful Company of Instrument Makers.
Abstract
The use of hybrid intelligent systems in industrial
and commercial applications is briefly reviewed. The potential for
application of such systems, in particular those that combine results
from several constituent classifiers, to problems in drug design is
discussed. It is shown that, although there are no general rules as to
how a number of classifiers should best be combined, effective
combinations can automatically be generated by genetic programming
(GP). A robust performance measure based on the area under classifier
receiver-operating-characteristic (ROC) curves is used as a fitness
measure in order to facilitate evolution of multi-classifier systems
that outperform their constituent individual classifiers. The approach
is illustrated by application to publicly available Landsat data and
to pharmaceutical data of the kind used in one stage of the drug
design process.
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