Skip to content

Latest commit

 

History

History
9 lines (7 loc) · 518 Bytes

File metadata and controls

9 lines (7 loc) · 518 Bytes

Project-Insurance-Decisioning

Problem Overview: The goal of this project is to build a predictive model that takes various inputs from customers and provides a risk classification for their life insurance application. The model should be able to accurately classify applicants into different risk categories while maintaining privacy and avoiding the need for extensive manual processes.

Model implemented

1.Random Forest

Model Explainability

Model Explainability and Interpretability with the help of SHAP.