Paper Title
Credit Card Fraud Detection System
Article Identifiers
Authors
P.N.Fale , Yash bandiwar , Pratik pillewan , Gaurav gokhale , Gaurav tarale
Keywords
credit card , machine learning
Abstract
In this review article, we'll talk about how machine learning can be used to spot credit card fraud. It is more crucial than ever to have precise mechanisms in place to spot fraudulent conduct given the rise in online transactions. The authors suggest applying machine learning techniques to pre-process data sets and analyze them to precisely identify fraudulent credit card transactions. While minimizing false positive fraud classifications, the goal is to identify 100% of fraudulent transactions. To accomplish this, the study focuses on employing anomaly detection methods on modified credit card transaction data.
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How To Cite
"Credit Card Fraud Detection System", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 5, page no.a448-a452, May-2023, Available :https://ijnrd.org/papers/IJNRD2305056.pdf
Issue
Volume 8 Issue 5, May-2023
Pages : a448-a452
Other Publication Details
Paper Reg. ID: IJNRD_192849
Published Paper Id: IJNRD2305056
Downloads: 000121123
Research Area: Engineering
Country: Nagpur, maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2305056.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305056
About Publisher
Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


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