INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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.
Keywords:
credit card , machine learning
Cite Article:
"Credit Card Fraud Detection System", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.a448-a452, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305056.pdf
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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
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