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1、IEEETRANSACTIONSONEVOLUTIONARYCOMPUTING,VOL.6,NO.4,AUGUST2002321DataMiningWithanAntColonyOptimizationAlgorithmRafaelS.Parpinelli,HeitorS.Lopes,Member,IEEE,andAlexA.FreitasAbstract—Thispaperproposesanalgorithmfordataminingonthevaluesofsomeattributes(c
2、alledpredictorattributes)forcalledAnt-Miner(ant-colony-baseddataminer).ThegoalofAnt-thecase.Mineristoextractclassificationrulesfromdata.ThealgorithmisInthecontextoftheclassificationtaskofdatamining,dis-inspiredbybothresearchonthebehaviorofrealantcolo
3、niesandcoveredknowledgeisoftenexpressedintheformofIF–THENsomedataminingconceptsaswellasprinciples.WecomparetheperformanceofAnt-MinerwithCN2,awell-knowndataminingrules,asfollows:algorithmforclassification,insixpublicdomaindatasets.There-sultsprovideev
4、idencethat:1)Ant-MineriscompetitivewithCN2withrespecttopredictiveaccuracyand2)therulelistsdiscoveredbyAnt-Minerareconsiderablysimpler(smaller)thanthosedis-Theruleantecedent(IFpart)containsasetofcondi-coveredbyCN2.tions,usuallyconnectedbyalogicalconju
5、nctionoperatorIndexTerms—Antcolonyoptimization,classification,data(AND).Wewillrefertoeachruleconditionasaterm,somining,knowledgediscovery.thattheruleantecedentisalogicalconjunctionoftermsintheform.EachtermI.INTRODUCTIONisatriple,suchas.NESSENCE,thego
6、alofdataminingistoextractknowledgeTheruleconsequent(THENpart)specifiestheclasspredictedIfromdata.Dataminingisaninterdisciplinaryfield,whoseforcaseswhosepredictorattributessatisfyallthetermsspeci-coreisattheintersectionofmachinelearning,statistics,and
7、fiedintheruleantecedent.Fromadata-miningviewpoint,thisdatabases.kindofknowledgerepresentationhastheadvantageofbeingin-Weemphasizethatindatamining—unlike,e.g.,classicalsta-tuitivelycomprehensiblefortheuser,aslongasthenumberoftistics—thegoalistodiscove
8、rknowledgethatisnotonlyac-discoveredrulesandthenumberoftermsinruleantecedentsarecurate,butalsocomprehensiblefortheuser[12],[13].Com-notlarge.prehensibilityisimportantwheneverdiscoveredknowledgewillTothebestofourknowledge,theuseofACOalgorithmsbeusedfo
