Mini-project
Insurance
Health insurance cost predictor
Predict health insurance costs from age, BMI, smoking and region.
The brief
A health insurer wants to understand what drives medical costs before it reprices its plans. Build regression models that predict yearly costs from customer details, explain which factors matter most, and show the effect of smoking and BMI clearly. Good looks like: a model compared with a simple baseline, honest error measures, and clear charts of the main drivers.
What you will build
- Explore costs and their skew
- Build linear, tree-based and boosted regression models
- Evaluate with cross-validation and error measures
- Explain the main cost drivers
- Build a small quote calculator
Free, open data to build it with
Check each dataset's licence before you publish your work. Your mentor gives your team its own version of the brief (data, scope or region), so every team's project is its own.