Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/34981
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Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Azevedo, Paulo J. | por |
dc.date.accessioned | 2015-04-27T11:00:05Z | - |
dc.date.available | 2015-04-27T11:00:05Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | Azevedo PJ. 2010. Rules for contrast sets. Intelligent Data Analysis. 14(6):623-640. | - |
dc.identifier.issn | 1088-467X | por |
dc.identifier.uri | https://hdl.handle.net/1822/34981 | - |
dc.description.abstract | In this paper we present a technique to derive rules describing contrast sets. Contrast sets are a formalism to represent groups diferences. We propose a novel approach to describe directional contrasts using rules where the contrasting efect is partitioned into pairs of groups. Our approach makes use of a directional Fisher Exact Test to and significant diferences across groups. We used a Bonferroni within search adjustment to control type I errors and a pruning technique to prevent derivation of non significant contrast set specializations. | por |
dc.description.sponsorship | Thanks to Prof. M. Pazzani for kindly providing the code for the STUCCO algorithm. This work was Supported by Fundacao Ciencia e Tecnologia, Project PFound, Project ProtUnf, FEDER and Programa de Financiamento Plurianual de Unidades de I & D. | por |
dc.language.iso | eng | por |
dc.publisher | IOS Press | por |
dc.rights | openAccess | por |
dc.subject | Contrast Sets | por |
dc.subject | association rules | por |
dc.subject | Fisher exact test | por |
dc.subject | Bonferroni adjustment | por |
dc.title | Rules for contrast sets | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.comments | 1661 | por |
sdum.publicationstatus | published | por |
oaire.citationStartPage | 1 | por |
oaire.citationEndPage | 31 | por |
oaire.citationIssue | 6 | por |
oaire.citationTitle | Intelligent Data Analysis | - |
oaire.citationVolume | 14 | por |
dc.identifier.doi | 10.3233/IDA-2010-0444 | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Intelligent Data Analysis | por |
Aparece nas coleções: | HASLab - Artigos em revistas internacionais |