Poster Print Size: Improving Credit Card Fraud DetecCon...
Transcript of Poster Print Size: Improving Credit Card Fraud DetecCon...
PosterPrintSize:Thispostertemplateis24”highby36”wide.Itcanbeusedtoprintanyposterwitha2:3aspectraAoincluding36x54and48x72.
Placeholders:ThevariouselementsincludedinthisposterareonesweoGenseeinmedical,research,andscienAficposters.Feelfreetoedit,move,add,anddeleteitems,orchangethelayouttosuityourneeds.Alwayscheckwithyourconferenceorganizerforspecificrequirements.
ImageQuality:YoucanplacedigitalphotosorlogoartinyourposterfilebyselecAngtheInsert,Picturecommand,orbyusingstandardcopy&paste.Forbestresults,allgraphicelementsshouldbeatleast150-200pixelsperinchintheirfinalprintedsize.Forinstance,a1600x1200pixelphotowillusuallylookfineupto8“-10”wideonyourprintedposter.Topreviewtheprintqualityofimages,selectamagnificaAonof100%whenpreviewingyourposter.Thiswillgiveyouagoodideaofwhatitwilllooklikeinprint.Ifyouarelayingoutalargeposterandusinghalf-scaledimensions,besuretopreviewyourgraphicsat200%toseethemattheirfinalprintedsize.
Pleasenotethatgraphicsfromwebsites(suchasthelogoonyourhospital'soruniversity'shomepage)willonlybe72dpiandnotsuitableforprinAng.
[Thissidebarareadoesnotprint.]
ChangeColorTheme:Thistemplateisdesignedtousethebuilt-incolorthemesinthenewerversionsofPowerPoint.Tochangethecolortheme,selecttheDesigntab,thenselecttheColorsdrop-downlist.
Thedefaultcolorthemeforthistemplateis“Office”,soyoucanalwaysreturntothataGertryingsomeofthealternaAves.
PrinAngYourPoster:Onceyourposterfileisready,visitwww.genigraphics.comtoorderahigh-quality,affordableposterprint.EveryorderreceivesafreedesignreviewandwecandeliverasfastasnextbusinessdaywithintheUSandCanada.Genigraphics®hasbeenproducingoutputfromPowerPoint®longerthananyoneintheindustry;daAngbacktowhenwehelpedMicrosoG®designthePowerPoint®soGware.
USandCanada:1-800-790-4001Email:[email protected]
[Thissidebarareadoesnotprint.]
ImprovingCreditCardFraudDetecConusingCNN/GAN
RajeshSabari,[email protected]
Contact1. S.Maes,K.Tuyls,B.Vanschoenwinkel,andB.Manderick,“CreditCardFraudDetecAonUsingBayesianandNeuralNetworks,”
2. K.Fu,D.Cheng,Y.Tu,andL.Zhang,“CreditCardFraudDetecAonUsingConvoluAonalNeuralNetworks,”
References
UsingGANfor5000roundspiqngthegeneratornetworkagainstthediscriminatornetwork,makinguseofthecross-entropylossfromthediscriminatortotrainthenetworksforimprovingclassificaAoneffecAvenessinCreditCardFraudDetecAon.Theaugmentedimageispassedthrough1x29convoluAonallayerfollowedbyafullyconnecteddenselayerstofinallyhaveaSoGmaxpredictor
MoCvaCon/Summary
Dataset
ThebaselinemodelswereLogisAcRegression,RandomForestandGaussianNB.3DLmodelsusedare2layerMLP,GAN,two1DConvlayer,maxpooling,afullyconnected(300neurons)andsoGmaxclassifier(2classes). prediction).
Models
CNN(bestperformance):0.860230099502RandomForestClassifier:0.846437(baseline)
MLPClassifier(2Layerwithdropout):0.8085106382978723MLPClassifier(1Layer):0.707243346007604
Discussion
CNNwithenhancedfrauddatasetthroughGANyieldedhightrainingandtestaccuracyonourtrainingandtestsets.AddingdropoutcertainlyyieldedlowervarianceandaddiAonallayersinMLPenhancedperformance.ThepoorgeneralizaAonisaresultofourdatasetnotbeingdiverse.Bytheendof5000trainingiteraAonsthegeneratedfraudimagedparernstartedtomimicactualfraud
Conclusions
ModelResults
DatasetsusedfortraininginthisprojectarefromKagglewith31featuresincludingtheAmeandamountoftransacAonaswellasalabelwhetherthattransacAonwasfraudulentornot.ThevariablesarePCAtransformed.99.83%oftransacAonsinthisdatasetwerenotfradulentwhileonly0.17%werefradulent