A Discrete Crow Search Algorithm for Mining Quantitative Association Rules
| dc.contributor.author | Abderrahim Siam | |
| dc.date.accessioned | 2024-03-13T20:34:32Z | |
| dc.date.available | 2024-03-13T20:34:32Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Associationrulesarethespecificdataminingmethodsaimingtodiscoverexplicitrelationsbetweenthe differentattributesinalargedataset.However,inreality,severaldatasetsmaycontainbothnumericand categoricalattributes.Recently,manymeta-heuristicalgorithmsthatmimicthenaturearedeveloped forsolvingcontinuousproblems.Thisarticleproposesanewalgorithm,DCSA-QAR,formining quantitativeassociationrulesbasedoncrowsearchalgorithm(CSA).Toaccomplishthis,newoperators aredefinedtoincreasetheabilitytoexplorethesearchingspaceandensurethetransitionfromthe continuoustothediscreteversionofCSA.Moreover,anewdiscretizationalgorithmisadoptedfor numericalattributestakingintoaccountdependenciesprobablythatexistbetweenattributes.Finally, toevaluatetheperformance,DCSA-QARiscomparedwithparticleswarmoptimizationandmono andmulti-objectiveevolutionaryapproachesforminingassociationrules.Theresultsobtainedover real-worlddatasetsshowtheoutstandingperformanceofDCSA-QARintermsofqualitymeasures. | |
| dc.identifier.uri | http://dspace.univ-khenchela.dz:4000/handle/123456789/4239 | |
| dc.language.iso | en | |
| dc.title | A Discrete Crow Search Algorithm for Mining Quantitative Association Rules |
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