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R Deep Learning Projects

You're reading from  R Deep Learning Projects

Product type Book
Published in Feb 2018
Publisher Packt
ISBN-13 9781788478403
Pages 258 pages
Edition 1st Edition
Languages

Credit card fraud detection with autoencoders


Fraud is a multi-billion dollar industry, with credit card fraud being probably the closest to our daily lives. Fraud begins with the theft of the physical credit card or with data that could compromise the security of the account, such as the credit card number, expiration date and security codes. A stolen card can be reported directly, if the victim knows that their card has been stolen, however, when the data is stolen, a compromised account can take weeks or even months to be used, and the victim then only knows from their bank statement that the card has been used. 

Traditionally, fraud detection systems rely on the creation of manually engineered features by subject matter experts, working either directly with financial institutions or with specialized software vendors. 

One of the biggest challenges in fraud detection is the availability of labelled datasets, which are often hard or even impossible to come by.

Our first fraud example comes...

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