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dc.contributor.authorGoy, Gokhan
dc.contributor.authorGezer, Cengiz
dc.contributor.authorGungor, Vehbi Cagri
dc.date.accessioned2021-04-22T08:08:54Z
dc.date.available2021-04-22T08:08:54Z
dc.date.issued01.01.2019en_US
dc.identifier.isbn978-1-7281-3964-7
dc.identifier.urihttps://hdl.handle.net/20.500.12573/667
dc.description.abstractWith the increase in credit card usage of people, the credit card transactions increase dramatically. It is difficult to identify fraudulent transactions among the vast amount of credit card transactions. Although credit card fraud is limited in number of transactions, it causes serious problems in terms of financial losses for individuals and organizations. Even though large number of studies has been conducted to solve this problem, there is no generally accepted solution. In this paper, a publicly available data set is used. The unbalance problem of the data set was solved by using hybrid sampling methods together. On this data set, comparative performance evaluations have been conducted. Different from other studies, the Area Under the Curve (AUC) metric, which expresses the success in such data sets, has also been used in addition to standard performance metrics. Since it is also important to quickly detect credit card fraud transactions; the running time of different methods is also presented as another performance metric.en_US
dc.description.sponsorshipIEEE; IEEE Turkey Secten_US
dc.language.isoturen_US
dc.publisherIEEE, 345 E 47TH ST, NEW YORK, NY 10017 USAen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBinary Classificationen_US
dc.subjectData Miningen_US
dc.subjectMachine Learningen_US
dc.subjectFraud Detectionen_US
dc.subjectCredit Carden_US
dc.titleCredit Card Fraud Detection with Machine Learning Methodsen_US
dc.typeconferenceObjecten_US
dc.contributor.departmentAGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.relation.journal2019 4TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ENGINEERING (UBMK)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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