Insurance Fraud Detection
In this project, I try to detect customers who have the potential to fraud at an insurance company. Exploratory data analysis and machine learning models were built and applied to this project.
The analysis is performed by exploring the overall data. Based on the exploration, we know that the data is imbalanced so it can be considered and processed further later. Then person correlation is performed to get the high-correlated columns. After that, some machine learning models are built and compared to others. The best machine learning model by the performance is chosen.