Show simple item record

dc.contributor.authorGrzymala-Busse, Jerzy W.
dc.contributor.authorThan, Soe
dc.date.accessioned2005-05-18T11:47:12Z
dc.date.available2005-05-18T11:47:12Z
dc.date.issued1996-12
dc.identifier.citationGrzymalaBusse, JW; Than, S. Partition triples: A tool for reduction of data sets. JOURNAL OF COMPUTER AND SYSTEM SCIENCES. Dec 1996. 53(3):575-582
dc.identifier.otherISI:A1996WB60900018
dc.identifier.urihttp://hdl.handle.net/1808/417
dc.description.abstractData sets discussed in this paper are presented as tables with rows corresponding to examples (entities, objects) and columns to attributes. A partition triple is defined for such a table as a triple of partitions on the set of examples, the set of attributes, and the set of attribute values, respectively, preserving the structure of a table. The idea of a partition triple is an extension of the idea of a partition pair, introduced by J. Hartmanis and J. Steams in automata theory. Results characterizing partition triples and algorithms for computing partition triples are presented. The theory is illustrated by an example of an application in machine learning from examples. (C) 1996 Academic Press, Inc.
dc.format.extent71642 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherACADEMIC PRESS INC JNL-COMP SUBSCRIPTIONS
dc.subjectTheory & methods
dc.subjectComputer science
dc.subjectHardware & architecture
dc.titlePartition triples: A tool for reduction of data sets
dc.typeArticle
dc.identifier.doi10.1006/jcss.1996.0088
dc.rights.accessrightsopenAccess


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record