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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Credit Card Fraud Detection using Ensemble Learning with Boosting Technique |
| Authors Name: | Mahmud Mustapha Gana , Mustapha Ismail , Audu Musa Mabu |
| Unique Id: | IJSDR2308172 |
| Published In: | Volume 8 Issue 8, August-2023 |
| Abstract: | This research paper proposes a novel approach for credit card fraud detection in the banking sector. The study utilizes ensemble learning with boosting techniques, combining the Random Forest(RF), Support Vector Machine(SVM), and Extreme Gradient Boosting(XGBoost) algorithms to create a powerful ensemble classifier. The approach is evaluated using an extensive dataset of credit card transactions. The results demonstrate exceptional recall, accuracy, precision, and F-score values with result of 1.0 for each evaluation metrics. In this study ensemble model developed outperforms previous studies by incorporating multiple evaluation measures and effectively leveraging the strengths of each base classifier. The research highlights the importance of considering a range of evaluation metrics and suggests avenues for further research in improving fraud detection systems. By addressing the limitations of earlier studies and using resampling techniques to handle imbalanced data, the proposed ensemble model offers significant potential for enhancing fraud detection and security protocols in the financial sector. The findings are considered trustworthy and have important implications for the industry, as they improve the realism and generalizability of credit card fraud detection through the use of the Kaggle.com dataset and ensemble learning techniques. |
| Keywords: | Credit Card Fraud, Ensemble Learning, Imbalanced Dataset, Boosting Technique & Machine learning |
| Cite Article: | "Credit Card Fraud Detection using Ensemble Learning with Boosting Technique", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 8, page no.1170 - 1179, August-2023, Available :http://www.ijsdr.org/papers/IJSDR2308172.pdf |
| Downloads: | 000338720 |
| Publication Details: | Published Paper ID: IJSDR2308172 Registration ID:208390 Published In: Volume 8 Issue 8, August-2023 DOI (Digital Object Identifier): Page No: 1170 - 1179 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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