Loan eligibility classification using logistic regression

• Main Authors: Lik Pao, Paul Law, Mohd Arfian, Ismail
• Format: Conference or Workshop Item
• Language: English; English
• Published: Institute of Electrical and Electronics Engineers Inc. 2023
• Subjects: Q Science (General); QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/40314/1/Loan%20eligibility%20classification%20using%20logistic%20regression.pdf; http://umpir.ump.edu.my/id/eprint/40314/2/Loan%20eligibility%20classification%20using%20logistic%20regression_ABS.pdf; http://umpir.ump.edu.my/id/eprint/40314/; https://doi.org/10.1109/ICSECS58457.2023.10256402

Machine learning is becoming increasingly vital in various domains, including loan eligibility classification, d ue to its ability to analyze large amounts of data, develop predictive models, adapt to new information, and automate processes. This research paper presents a study on loan eligibility c...