Commercial banks receive a lot of applications for credit cards. Manually analyzing these applications is error-prone, and time-consuming. We can automate the task using machine learning. We can do so ...

This project focuses on predicting credit card approval using machine learning techniques. It involves data preprocessing, exploratory data analysis (EDA), model training, evaluation, and deployment.

Automation of the credit card application approval process is being ... can adversely impact the performance of Machine Learning (ML) algorithms. Data preprocessing plays a crucial role in enhancing ...

Abstract: Credit ... single-model approaches in precision, recall, F1-score, AUC, and Kappa, providing a robust and scalable solution for credit card approval predictions. This research underscores ...