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Discovering Multi-head Attributional Rules in Large Databases

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dc.contributor.author Głowiński, Cezary
dc.contributor.author Michalski, Ryszard S.
dc.date.accessioned 2006-11-03T18:17:14Z
dc.date.available 2006-11-03T18:17:14Z
dc.date.issued 2001-06 en_US
dc.identifier.citation (P 01-4) Glowinski, C. and Michalski, R. S., "Discovering Multi-head Attributional Rules in Large Databases," Tenth International Symposium on Intelligent Information Systems, Zakopane, Poland, June, 2001. en_US
dc.identifier.uri https://hdl.handle.net/1920/1475
dc.description.abstract A method for discovering multi-head attributional rules in large databases is presented and illustrated by results from an implemented program. Attributional rules (a.k.a. attributional dependencies) can be viewed as generalizations of standard association rules, because they use more general and expressive conditions than those in the latter ones, and by that can express more concisely inter-attribute relations in a database. Multi-head rules have multiple conditions/statements in their conclusion. The presented method applies AQ learning to create single-head characteristic rules, and then seeks conditions (selectors) that can be transferred to the conclusion part of the rule. Experiments with the program MAR1 (Multi-Head Attributional Rules), implementing the developed method, has produced highly encouraging results.
dc.description.sponsorship Cezary Głowiński has been supported by Kosciuszko Foundation in New York, in part by the National Science Foundation Grant IIS 9906858, and in part by the UMBC/MPO/Lucite #32 grant. en_US
dc.format.extent 2060 bytes
dc.format.extent 237901 bytes
dc.format.extent 61973 bytes
dc.format.mimetype text/xml
dc.format.mimetype application/postscript
dc.format.mimetype application/pdf
dc.language.iso en_US en_US
dc.relation.ispartofseries P 01-4 en_US
dc.subject attributional rules en_US
dc.title Discovering Multi-head Attributional Rules in Large Databases en_US
dc.type Presentation en_US


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