Comparative Assessment of Fraudulent Financial Transactions using the Machine Learning Algorithms Decision Tree, Logistic Regression, Naïve Bayes, K-Nearest Neighbor, and Random Forest
Today, fast-paced technology plays an important role in financial transactions, especially in payment-related digital habits. As fraud is a major concern in online payments, many machine-learning approaches have been proposed to detect and prevent fraudulent payment transactions. This study aimed to...
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| Published in: | Engineering, technology & applied science research Vol. 14; no. 4; pp. 15676 - 15680 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
02.08.2024
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| ISSN: | 2241-4487, 1792-8036 |
| Online Access: | Get full text |
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