Association Rules and Statistics
Identifieur interne : 004987 ( Hal/Checkpoint ); précédent : 004986; suivant : 004988Association Rules and Statistics
Auteurs : Martine Cadot [France] ; Jean-Baptiste Maj [France] ; Tarek ZiadéSource :
English descriptors
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Abstract
In this paper, the two kinds of knowledge extracted by Statistics and by Association Rules, both working on the same data structured in tables [Objects *x* Properties], are compared. These two methods establish the links between properties of objects. When the amount of data properties increases, Statistics may be replaced by Association rules for better performance. Pros and cons of using Association rules instead of Statistics are described in this paper.
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Hal:hal-00014700Le document en format XML
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and by Association Rules, both working on the same data structured in tables [Objects *x* Properties], are compared. These two methods establish the links between properties of objects. When the amount of data properties increases, Statistics may be replaced by Association rules for better performance. Pros and cons of using Association rules instead of Statistics are described in this paper.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Association Rules and Statistics</title><author role="aut"><persName><forename type="first">Martine</forename><surname>Cadot</surname></persName><email>martine.cadot@loria.fr</email><idno type="halauthor">71804</idno><affiliation ref="#struct-2359"></affiliation></author><author role="aut"><persName><forename type="first">Jean-Baptiste</forename><surname>Maj</surname></persName><email>JBMaj@Loria.fr</email><idno type="halauthor">71805</idno><affiliation ref="#struct-2359"></affiliation></author><author role="aut"><persName><forename type="first">Tarek</forename><surname>Ziadé</surname></persName><email>tarek@ziade.org</email><idno type="halauthor">71806</idno></author><editor role="depositor"><persName><forename>Jean Baptiste</forename><surname>Maj</surname></persName><email>JBMaj@Loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2005-12-02 10:23:31</date><date type="whenModified">2016-05-18 09:00:59</date><date type="whenReleased">2005-12-02 10:23:31</date><date type="whenProduced">2005</date></edition><respStmt><resp>contributor</resp><name key="107446"><persName><forename>Jean Baptiste</forename><surname>Maj</surname></persName><email>JBMaj@Loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-00014700</idno><idno type="halUri">https://hal.archives-ouvertes.fr/hal-00014700</idno><idno type="halBibtex">cadot:hal-00014700</idno><idno type="halRefHtml">John Wang, Montclair State University, USA. Encyclopedia of Data Warehousing and Mining, Idea Group Inc., pp.74--77, 2005, Vol. 1</idno><idno type="halRef">John Wang, Montclair State University, USA. Encyclopedia of Data Warehousing and Mining, Idea Group Inc., pp.74--77, 2005, Vol. 1</idno></publicationStmt><seriesStmt><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno><idno type="stamp" n="INSMI">CNRS-INSMI - INstitut des Sciences Mathématiques et de leurs Interactions</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="LORIA-TALC" p="LORIA">Traitement automatique des langues et des connaissances</idno><idno type="stamp" n="INRIA2">INRIA 2</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="commentary">4 pages - ISBN : 1-59140-557-2</note><note type="audience" n="0">Not set</note><note type="popular" n="0">No</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Association Rules and Statistics</title><author role="aut"><persName><forename type="first">Martine</forename><surname>Cadot</surname></persName><email>martine.cadot@loria.fr</email><idno type="halAuthorId">71804</idno><affiliation ref="#struct-2359"></affiliation></author><author role="aut"><persName><forename type="first">Jean-Baptiste</forename><surname>Maj</surname></persName><email>JBMaj@Loria.fr</email><idno type="halAuthorId">71805</idno><affiliation ref="#struct-2359"></affiliation></author><author role="aut"><persName><forename type="first">Tarek</forename><surname>Ziadé</surname></persName><email>tarek@ziade.org</email><idno type="halAuthorId">71806</idno></author></analytic><monogr><title level="m">Encyclopedia of Data Warehousing and Mining</title><editor>John Wang, Montclair State University, USA</editor><imprint><publisher>Idea Group Inc.</publisher><biblScope unit="serie">Vol. 1</biblScope><biblScope unit="pp">74--77</biblScope><date type="datePub">2005</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">association rules</term><term xml:lang="en">statistics</term></keywords><classCode scheme="halDomain" n="math.math-st">Mathematics [math]/Statistics [math.ST]</classCode><classCode scheme="halDomain" n="spi.other">Engineering Sciences [physics]/Other</classCode><classCode scheme="halDomain" n="info.info-lg">Computer Science [cs]/Machine Learning [cs.LG]</classCode><classCode scheme="halDomain" n="info.info-ai">Computer Science [cs]/Artificial Intelligence [cs.AI]</classCode><classCode scheme="halDomain" n="info.info-ir">Computer Science [cs]/Information Retrieval [cs.IR]</classCode><classCode scheme="halDomain" n="info.info-ds">Computer Science [cs]/Data Structures and Algorithms [cs.DS]</classCode><classCode scheme="halTypology" n="COUV">Book section</classCode></textClass><abstract xml:lang="en">In this paper, the two kinds of knowledge extracted by Statistics and by Association Rules, both working on the same data structured in tables [Objects *x* Properties], are compared. These two methods establish the links between properties of objects. When the amount of data properties increases, Statistics may be replaced by Association rules for better performance. Pros and cons of using Association rules instead of Statistics are described in this paper.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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