A Hybrid heuristic-exhaustive search approach for rule extraction

dc.contributor.advisorEngelbrecht, Andries P.en
dc.contributor.postgraduateRodic, Danielen
dc.date.accessioned2013-09-06T19:11:51Z
dc.date.available2006-06-05en
dc.date.available2013-09-06T19:11:51Z
dc.date.created2001-04-01en
dc.date.issued2007-06-05en
dc.date.submitted2006-05-29en
dc.descriptionDissertation (MSc)--University of Pretoria, 2007.en
dc.description.abstractThe topic of this thesis is knowledge discovery and artificial intelligence based knowledge discovery algorithms. The knowledge discovery process and associated problems are discussed, followed by an overview of three classes of artificial intelligence based knowledge discovery algorithms. Typical representatives of each of these classes are presented and discussed in greater detail. Then a new knowledge discovery algorithm, called Hybrid Classifier System (HCS), is presented. The guiding concept behind the new algorithm was simplicity. The new knowledge discovery algorithm is loosely based on schemata theory. It is evaluated against one of the discussed algorithms from each class, namely: CN2; C4.5, BRAINNE and BGP. Results are discussed and compared. A comparison was done using a benchmark of classification problems. These results show that the new knowledge discovery algorithm performs satisfactory, yielding accurate, crisp rule sets. Probably the main strength of the HCS algorithm is its simplicity, so it can be the foundation for many possible future extensions. Some of the possible extensions of the new proposed algorithm are suggested in the final part of this thesis.en
dc.description.availabilityunrestricteden
dc.description.departmentComputer Scienceen
dc.identifier.citationRodic, D 2000, A hybrid heuristic-exhaustive search approach for rule extraction, MEng dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://hdl.handle.net/2263/25095 >en
dc.identifier.otherH558/agen
dc.identifier.upetdurlhttp://upetd.up.ac.za/thesis/available/etd-05292006-110006/en
dc.identifier.urihttp://hdl.handle.net/2263/25095
dc.language.isoen
dc.publisherUniversity of Pretoriaen_ZA
dc.rights© 2000, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.en
dc.subjectHybrid classifier systemen
dc.subjectArtificial intelligenceen
dc.subjectData mining algorithmsen
dc.subjectHcsen
dc.subjectAutomated knowledgeen
dc.subjectUCTDen_US
dc.titleA Hybrid heuristic-exhaustive search approach for rule extractionen
dc.typeDissertationen

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