Outlier detection using ball descriptions with adjustable metric

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Published Date

2006

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Undefined/Unknown

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Abstract

Sometimesnoveloroutlierdatahastobedetected.Theoutliersmayindicatesomeinterestingrareevent,ortheyshouldbedisregardedbecausetheycannotbereliablyprocessedfurther.Intheidealcasethattheobjectsarerepresentedbyverygoodfeatures,thegenuinedataformsacompactclusterandagoodoutliermeasureisthedistancetotheclustercenter.Thispaperproposesthreenewformulationsto¿ndagoodclustercentertogetherwithanoptimizedp-distancemeasure.Experimentsshowthatforsomerealworlddatasetsverygoodclassi¿cationresultsareobtainedandthat,morespeci¿cally,the1-distanceisparticularlysuitedfordatasetscontainingdiscretefeaturevalues.