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Now a days, the problem of credit card fraud is constantly increasing. All these problems are constantly happening due to rapid increase in the payment process. Credit card fraud occurs when someone's credit card is lost or in the hands of an unknown person. And they use the found credit card in a fake way .Nowadays many people are struggling with these kinds of problems. So this project is designed to avoid credit card frauds. This is the application of data sciences. The main focus of this project is to use machine learning algorithms. In this we will use Isolation Forest and Local Outlier Factor Algorithms. The results are in these algorithms is based on accuracy, precision, recall and F1 score
Keywords:
Credit card fraudulent, Application of data science, isolation forest, Outlier Factor
Cite Article:
"Machine learning algorithms for Credit card fraud prevention and detection", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.6, Issue 7, page no.101 - 107, July-2021, Available :http://www.ijrti.org/papers/IJSDR2107018.pdf
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000204759
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator