Smart Fraud Detection in E-Commerce Using Machine Learning

Machine Learning is an area of focus within Artificial Intelligence which has received considerable attention as part of the solutions to the digital transformation problem in the modern world. This paper attempts to review some of the most popular and frequently used machine learning algorithms. The author seeks to assist in decision making by highlighting the advantages and disadvantages of machine learning algorithms with respect to applications so that appropriate decisions can be made with respect to the chosen algorithm for the specific requirements of the application.

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-05-20
DOI
https://doi.org/10.22214/ijraset.2025.71303
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Fraud Detection in E-Commerce Using Machine Learning

K. Dasarathi Shohi
International Journal for Research in Applied Science and Engineering Technology
Imbalanced Data Classification Techniques
article

Smart Fraud Detection in E-Commerce Using Machine Learning

K. Dasarathi Shohi
article en

Abstract

Machine Learning is an area of focus within Artificial Intelligence which has received considerable attention as part of the solutions to the digital transformation problem in the modern world. This paper attempts to review some of the most popular and frequently used machine learning algorithms. The author seeks to assist in decision making by highlighting the advantages and disadvantages of machine learning algorithms with respect to applications so that appropriate decisions can be made with respect to the chosen algorithm for the specific requirements of the application.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(5)
Openalex Percentile: Top 95%
Imbalanced Data Classification Techniques
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Smart Fraud Detection in E-Commerce Using Machine Learning — K. Dasarathi Shohi · International Journal for Research in Applied Science and Engineering Technology (2025) | TGRS Research Map | TGRS