#Model-Training- https://github.com/DaBestCode/Machine-learning-model-training
🏥 Health Insurance Premium Predictor A machine learning web app built with Streamlit that predicts the cost of healthcare insurance premiums for individuals based on a variety of demographic, lifestyle, and medical factors.
🚀 Project Highlights Deployed with Streamlit for instant, interactive web-based predictions.
Trained model on preprocessed features including:
Demographics: age, gender, region, marital status, number of dependents
Financial: income (in lakhs), employment status
Health: BMI category, smoking status, genetical risk, normalized risk score
Insurance plan type: insurance_plan
🧠 Features Used text Copy code
- age
- number_of_dependants
- income_lakhs
- insurance_plan
- genetical_risk
- normalized_risk_score
- gender_Male
- region_Northwest, region_Southeast, region_Southwest
- marital_status_Unmarried
- bmi_category_Obesity, Overweight, Underweight
- smoking_status_Occasional, Regular
- employment_status_Salaried, Self-Employed 📦 Tech Stack Python, Pandas, scikit-learn
Streamlit for front-end deployment
Model serialization with joblib
🔮 Use Case This app can help:
Insurance companies price premiums more accurately
Individuals estimate expected premium costs
Data scientists explore ML applications in health insurance