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  Published Paper Details:

  Paper Title

FRAUD IDENTIFICATION OF CREDIT CARD USING MACHINE LEARNING

  Authors

  Nayana B M,  Namratha M N,  K Vishnuvardhan,  Gani Prabhakar,  Rekha Jayaram

  Keywords

Credit card fraud, logistic regression, random forest

  Abstract


Online Transaction is a popular mode of payment and most of the payments done by using credit card but credit card fraud happens continuously and it leads to huge lose. So all the banks and other financial industries supports to the progress of Fraud identification of credit card. The fraudulent transactions can takes place in different ways, identification of credit card fraud is very important to the credit card companies so that customers will not be charged for the items those are not purchased. This paper explained the concepts related to credit card and used different machine learning algorithms like logistic regression and random forest method .2,84,808 credit card transactions of dataset is collected from kaggle and these transactions are from European bank. Identification of credit card is an example of classification and in this process includes analyzing and preprocessing the data set along with the deployment of Machine learning algorithms.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2106160

  Paper ID - 208433

  Page Number(s) - b307-b311

  Pubished in - Volume 9 | Issue 6 | June 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Nayana B M,  Namratha M N,  K Vishnuvardhan,  Gani Prabhakar,  Rekha Jayaram,   "FRAUD IDENTIFICATION OF CREDIT CARD USING MACHINE LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 6, pp.b307-b311, June 2021, Available at :http://www.ijcrt.org/papers/IJCRT2106160.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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