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Research Article
A Comparative Study on Loan Status: Utilizing Machine Learning Algorithms for Predictive Analysis
Thanneeru Mahesh1
B.Tech, Computer Science and Engineering, University College of Engineering, Narasaropet JNTUK, Narasaraopet, Andhra Pradesh, India.
Published Online: January-February 2024
Pages: 09-12
Cite this article
↗ https://www.doi.org/10.59256/ijsreat.20240401003
References
1. Zhang, L., Dong, Y., & He, J. (2020). Loan Approval Prediction Using Random Forest Algorithm. Journal of Physics: Conference Series,
1634(1).
2. Thomas, L. C., Edelman, D. B., & Crook, J. N. (2019). Credit Scoring and Its Applications (2nd ed.). SIAM.
3. Lee, H., Lee, H., & Choi, B. (2018). Loan default prediction modeling using deep learning: A comparative study. Applied Soft Computing,
68, 1067-1075.
4. Chen, J., Song, X., Wamba, S. F., & Cao, J. (2017). Research on credit scoring model based on support vector machine ensemble.
Electronic Commerce Research and Applications, 26, 1-12.
1634(1).
2. Thomas, L. C., Edelman, D. B., & Crook, J. N. (2019). Credit Scoring and Its Applications (2nd ed.). SIAM.
3. Lee, H., Lee, H., & Choi, B. (2018). Loan default prediction modeling using deep learning: A comparative study. Applied Soft Computing,
68, 1067-1075.
4. Chen, J., Song, X., Wamba, S. F., & Cao, J. (2017). Research on credit scoring model based on support vector machine ensemble.
Electronic Commerce Research and Applications, 26, 1-12.
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