Tools Used: Python,Ms-Excel
Algorithms Used
-Simple Linear Regression
-Logistic Regression
-K-Nearest Neighbour
-Support Vector Machine
-Random Forest
-Decision Tree
-Artificial Neural Network
In the domain of financial lending, accurately predicting loan repayment is a critical task for financial institutions. This project aims to develop a loan repayment system that utilizes machine learning algorithms to predict the risk of loan default and manage repayment processes effectively.
📈 Results Snapshot
-Logistic Regression: Accuracy - 77.78%, Precision - 78.77%
-K-Nearest Neighbour: Accuracy - 86.67%, Precision - 75.58%
-Support Vector Machine: Accuracy - 84.44%, Precision - 85.11%
-Random Forest: Accuracy - 84.44%, Precision - 84.49%
-Decision Tree: Accuracy - 82.22%, Precision - 80.6%
-Artificial Neural Network-71.33%