Title page for ETD etd-05292006-110006


Document Type Master's Dissertation
Author Rodic, Daniel
URN etd-05292006-110006
Document Title A Hybrid heuristic-exhaustive search approach for rule extraction
Degree MSc (Computer Science)
Department Computer Science
Supervisor
Advisor Name Title
Prof A P Engelbrecht Committee Chair
Keywords
  • hybrid classifier system
  • artificial intelligence
  • data mining algorithms
  • HCS
  • automated knowledge
Date 2001-04-01
Availability unrestricted
Abstract
The 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.

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.

Please cite as follows:

Rodic, D 2000, A hybrid heuristic-exhaustive search approach for rule extraction, MEng dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-05292006-110006/ >

H558/ag

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