Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/33812
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Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Jorge, Alípio M. | por |
dc.contributor.author | Azevedo, Paulo J. | por |
dc.date.accessioned | 2015-02-12T10:57:23Z | - |
dc.date.available | 2015-02-12T10:57:23Z | - |
dc.date.issued | 2012 | - |
dc.identifier.issn | 1088-467X | - |
dc.identifier.issn | 1571-4128 | - |
dc.identifier.uri | https://hdl.handle.net/1822/33812 | - |
dc.description.abstract | In this paper we propose a framework for defining and discovering optimal association rules involving a numerical attribute A in the consequent. The consequent has the form of interval conditions A, A≥ x or A ∈ I where I is an interval or a set of intervals of the form [x_l,x_u. The optimality is with respect to leverage, one well known association rule interest measure. The generated rules are called Maximal Leverage Rules MLR and are generated from Distribution Rules. The principle for finding the MLR is related to the Kolmogorov-Smirnov goodness of fit statistical test. We propose different methods for MLR generation, taking into account leverage optimallity and readability. We theoretically demonstrate the optimality of the main exact methods, and measure the leverage loss of approximate methods. We show empirically that the discovery process is scalable. | por |
dc.description.sponsorship | This work was partially supported by the FCT project MORWAQ (PTDC/EIA/68489/2006) and by Fundacao Ciencia e Tecnologia, FEDER e Programa de Financiamento Plurianual de Unidades de I & D. Special thanks to Brett Drury for giving some suggestions regarding the wording of two paragraphs. | por |
dc.language.iso | eng | por |
dc.publisher | IOS Press | por |
dc.rights | openAccess | por |
dc.subject | Numerical association rules | por |
dc.subject | Leverage | por |
dc.subject | Optimal association rules. | por |
dc.subject | Distribution rules | por |
dc.title | Optimal leverage association rules with numerical interval conditions | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.comments | 1032 | por |
sdum.publicationstatus | published | por |
oaire.citationStartPage | 25 | por |
oaire.citationEndPage | 47 | por |
oaire.citationIssue | 1 | por |
oaire.citationTitle | Intelligent Data Analysis | por |
oaire.citationVolume | 16 | por |
dc.identifier.doi | 10.3233/IDA-2011-0509 | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Intelligent Data Analysis | por |
Aparece nas coleções: | HASLab - Artigos em revistas internacionais |