Abstract
In developing countries, credit card fraud continues to be a menace. We have to encounter this menace to emancipate humans from being the victims of credit card frauds. The most effective and powerful tool, i.e., data mining, is used by many researchers nowadays to detect and unmask the credit card frauds. Previously, many data mining algorithms were used for detecting credit card fraud. We pose a novel data mining algorithm called condensed nearest neighbor (CNN) algorithm to detect the credit card fraud. CNN algorithm is a nonparametric method used for classification. By using data reduction concept, CNN algorithm aims to form a condensed set by retaining the samples that are important in decision making.
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Vardhani, P.R., Priyadarshini, Y.I., Narasimhulu, Y. (2019). CNN Data Mining Algorithm for Detecting Credit Card Fraud. In: Soft Computing and Medical Bioinformatics. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-13-0059-2_10
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DOI: https://doi.org/10.1007/978-981-13-0059-2_10
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Publisher Name: Springer, Singapore
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Online ISBN: 978-981-13-0059-2
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