DC Field | Value | Language |
---|---|---|
dc.contributor.author | Bang, Won-Chul | ko |
dc.contributor.author | Bien, Zeung nam | ko |
dc.date.accessioned | 2013-03-06T05:35:22Z | - |
dc.date.available | 2013-03-06T05:35:22Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2001-12 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF FUZZY LOGIC AND INTELLIGENT SYSTEMS, v.11, no.7, pp.666 - 674 | - |
dc.identifier.issn | 1598-2645 | - |
dc.identifier.uri | http://hdl.handle.net/10203/85973 | - |
dc.description.abstract | Classical methods to :find a minimal set of rules based on the rough set theory are known to be ineffective in dealing with new instances added to the universe. This paper introduces an inductive learning algorithm for incrementally retrieving a minimal set of rules from a given decision table. Then, the algorithm is validated via simulations with two sets of data, in comparison with a classical non-incremental algorithm. The simulation results show that the proposed algorithm is effective in dealing with new instances, especially in practical use. | - |
dc.language | English | - |
dc.publisher | 한국지능시스템학회 | - |
dc.title | Rough Set-based Incremental Inductive Learning Algorithm - Theory and Applications | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.volume | 11 | - |
dc.citation.issue | 7 | - |
dc.citation.beginningpage | 666 | - |
dc.citation.endingpage | 674 | - |
dc.citation.publicationname | INTERNATIONAL JOURNAL OF FUZZY LOGIC AND INTELLIGENT SYSTEMS | - |
dc.contributor.localauthor | Bien, Zeung nam | - |
dc.contributor.nonIdAuthor | Bang, Won-Chul | - |
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