UGC Approved Journal no 63975(19)

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Published in:

Volume 8 Issue 6
June-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2106367


Registration ID:
310886

Page Number

c691-c694

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Title

credit card fraud detection using machine learning

Abstract

The use of credit cards to make large-scale online purchases online and systematically increases the number of fraudulent transactions that occur every day. Fraudulent credit card transactions occur intermittently and then cause huge financial difficulties. Criminals can use various methods such as phishing to steal credit card information from strangers, which requires an inappropriate method is to use historical data transactions, including repeated transactions and fraudulent transactions. This research paper uses machine learning here, which includes supervised learning algorithms such as random forest, decision tree, logistic regression, and Naïve Bayes to identify fraudulent transactions. This data set is collected by Kaggle and contains a total of 2,84,808 transactions. Treat fraudulent transactions as positive and real transactions as negative. Oversampling this to balance the dataset.

Key Words

random forest, naive bayes, logistic regression, decision tree

Cite This Article

"credit card fraud detection using machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.c691-c694, June-2021, Available :http://www.jetir.org/papers/JETIR2106367.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"credit card fraud detection using machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppc691-c694, June-2021, Available at : http://www.jetir.org/papers/JETIR2106367.pdf

Publication Details

Published Paper ID: JETIR2106367
Registration ID: 310886
Published In: Volume 8 | Issue 6 | Year June-2021
DOI (Digital Object Identifier):
Page No: c691-c694
Country: Bengaluru Rural, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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