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TCW Landgrebe
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1
Consideringtheclassi¿cationprobleminwhichclasspriorsormisallocationcostsarenotknownprecisely,receiveroperatorcharacteristic(ROC)analysishasbecomeastandardtoolinpatternrecognitionforobtainingintegratedperformancemeasurestocopewiththeuncertainty.Similarly,insituationsinwhichpriorsmayvaryinapplication,theROCcanbeusedtoinspectperformanceovertheexpectedrangeofvariation.InthispaperwearguethateventhoughmeasuressuchastheareaundertheROC(AUC)areusefulinobtaininganintegratedperformancemeasureindependentofthepriors,itmayalsobeimportanttoincorporatethesensitivityacrosstheexpectedprior-range.Weshowthataclassi¿ermayresultinagoodAUCscore,butapoor(large)priorsensitivity,whichmaybeundesirable.Amethodologyisproposedthatcombinesbothaccuracyandsensitivity,providinganewmodelselectioncriterionthatisrelevanttocertainproblems.Experimentsshowthatincorporatingsensitivityisveryimportantinsomerealisticscenarios,leadingtobettermodelselectioninsomecases
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Consideringtheclassi¿cationprobleminwhichclasspriorsormisallocationcostsarenotknownprecisely,receiveroperatorcharacteristic(ROC)analysishasbecomeastandardtoolinpatternrecognitionforobtainingintegratedperformancemeasurestocopewiththeuncertainty.Similarly,insituationsinwhichpriorsmayvaryinapplication,theROCcanbeusedtoinspectperformanceovertheexpectedrangeofvariation.InthispaperwearguethateventhoughmeasuressuchastheareaundertheROC(AUC)areusefulinobtaininganintegratedperformancemeasureindependentofthepriors,itmayalsobeimportanttoincorporatethesensitivityacrosstheexpectedprior-range.Weshowthataclassi¿ermayresultinagoodAUCscore,butapoor(large)priorsensitivity,whichmaybeundesirable.Amethodologyisproposedthatcombinesbothaccuracyandsensitivity,providinganewmodelselectioncriterionthatisrelevanttocertainproblems.Experimentsshowthatincorporatingsensitivityisveryimportantinsomerealisticscenarios,leadingtobettermodelselectioninsomecases