Synopsis
Financial fraud is an ever-growing menace with far consequences in the financial industry. Data mining had played an imperative role in the detection of ATM card fraud in online transactions. ATM card fraud detection, which is a data mining problem, becomes challenging due to two major reasons — first, the profiles of normal and fraudulent behaviors change constantly and secondly, ATM card fraud datasets are highly skewed. The performance of fraud detection in ATM card transactions are greatly affected by the sampling approach on the dataset, selection of variables and detection technique(s) used. This project investigates the performance of naïve bayes, k-nearest neighbor and logistic regression on highly skewed ATM card fraud data. We build and present a machine learning model to analyze & predict fraudulent transactions. The work is implemented in R, which is a programming language for statistical computing and graphics.
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ATM CARD Fraud Detection Using Machine Learning
Edité par
LAP LAMBERT Academic Publishing Feb 2019, 2019
ISBN 10 : 6139445361
ISBN 13 : 9786139445363
Neuf
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Financial fraud is an ever-growing menace with far consequences in the financial industry. Data mining had played an imperative role in the detection of ATM card fraud in online transactions. ATM card fraud detection, which is a data mining problem, becomes challenging due to two major reasons - first, the profiles of normal and fraudulent behaviors change constantly and secondly, ATM card fraud datasets are highly skewed. The performance of fraud detection in ATM card transactions are greatly affected by the sampling approach on the dataset, selection of variables and detection technique(s) used. This project investigates the performance of naïve bayes, k-nearest neighbor and logistic regression on highly skewed ATM card fraud data. We build and present a machine learning model to analyze & predict fraudulent transactions. The work is implemented in R, which is a programming language for statistical computing and graphics. 56 pp. Englisch. N° de réf. du vendeur 9786139445363
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ATM CARD Fraud Detection Using Machine Learning
Edité par
LAP LAMBERT Academic Publishing, 2019
ISBN 10 : 6139445361
ISBN 13 : 9786139445363
Neuf
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Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Siddanthapu Sai Harsha KiranG Venu Madhava Murthy is working as an ETL developer, P Ashok is working as a .NET developer, B Pavan is working as a PL/SQL developer, S Sai Harsha Kiran is working as an Augmented Reality and Virtual Rea. N° de réf. du vendeur 385858298
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ATM CARD Fraud Detection Using Machine Learning
Edité par
LAP LAMBERT Academic Publishing Feb 2019, 2019
ISBN 10 : 6139445361
ISBN 13 : 9786139445363
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Financial fraud is an ever-growing menace with far consequences in the financial industry. Data mining had played an imperative role in the detection of ATM card fraud in online transactions. ATM card fraud detection, which is a data mining problem, becomes challenging due to two major reasons - first, the profiles of normal and fraudulent behaviors change constantly and secondly, ATM card fraud datasets are highly skewed. The performance of fraud detection in ATM card transactions are greatly affected by the sampling approach on the dataset, selection of variables and detection technique(s) used. This project investigates the performance of naïve bayes, k-nearest neighbor and logistic regression on highly skewed ATM card fraud data. We build and present a machine learning model to analyze & predict fraudulent transactions. The work is implemented in R, which is a programming language for statistical computing and graphics.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch. N° de réf. du vendeur 9786139445363
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ATM CARD Fraud Detection Using Machine Learning
Edité par
LAP LAMBERT Academic Publishing, 2019
ISBN 10 : 6139445361
ISBN 13 : 9786139445363
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Financial fraud is an ever-growing menace with far consequences in the financial industry. Data mining had played an imperative role in the detection of ATM card fraud in online transactions. ATM card fraud detection, which is a data mining problem, becomes challenging due to two major reasons - first, the profiles of normal and fraudulent behaviors change constantly and secondly, ATM card fraud datasets are highly skewed. The performance of fraud detection in ATM card transactions are greatly affected by the sampling approach on the dataset, selection of variables and detection technique(s) used. This project investigates the performance of naïve bayes, k-nearest neighbor and logistic regression on highly skewed ATM card fraud data. We build and present a machine learning model to analyze & predict fraudulent transactions. The work is implemented in R, which is a programming language for statistical computing and graphics. N° de réf. du vendeur 9786139445363
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ATM CARD Fraud Detection Using Machine Learning
Edité par
LAP LAMBERT Academic Publishing, 2019
ISBN 10 : 6139445361
ISBN 13 : 9786139445363
Neuf
Taschenbuch
Vendeur : preigu, Osnabrück, Allemagne
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Taschenbuch. Etat : Neu. ATM CARD Fraud Detection Using Machine Learning | Sai Harsha Kiran Siddanthapu (u. a.) | Taschenbuch | 56 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139445363 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 115846603
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