IMPROVED LOAN PREDICTION SYSTEM USING MACHINE LEARNING
Keywords:Loan Prediction, Machine Learning
The aim of this project is to create a ensemble machine learning model that can determine whether a user is eligible for a loan. It is calculated using the user's personal data from the dataset such as education, number of dependents, income, loan amount,marital status, credit history, and work history. A data set of 600 instances is employed, with 70% of them being approved and the rest being refused. This ensemble algorithm helps in determining the applicant's ability to repay his or her loan. The prediction model benefits both the applicant and the bank by lowering risk and lowering the number of defaulters. The study will begin with exploratory data analysis, followed by preprocessing and testing in a developed hybrid machine learning model.