- Title
- Optimization of multiple classifiers in data mining based on string rewriting systems
- Creator
- Dazeley, Richard; Kelarev, Andrei; Yearwood, John; Mammadov, Musa
- Date
- 2009
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/59062
- Identifier
- vital:2275
- Identifier
- https://www.worldscinet.com/aejm/02/preserved-docs/0201/S1793557109000042.pdf
- Identifier
- ISSN:1793-5571
- Abstract
- Optimization of multiple classifiers is an important problem in data mining. We introduce additional structure on the class sets of the classifiers using string rewriting systems with a convenient matrix representation. The aim of the present paper is to develop an efficient algorithm for the optimization of the number of errors of individual classifiers, which can be corrected by these multiple classifiers.
- Relation
- Asian-European Journal of Mathematics Vol. 2, no. 1 (2009), p. 41-56; https://purl.org/au-research/grants/arc/DP0211866; https://purl.org/au-research/grants/arc/LP0669752
- Rights
- Open Access
- Rights
- Copyright World Scientific Publishing
- Rights
- This metadata is freely available under a CCO license
- Subject
- Optimization; Multiple classifiers; String rewriting systems
- Full Text
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