roshancyriacmathew/Medical-insurance-cost-prediction-using-linear-regression
This project explains on how to build a machine learning algorithm for calculating the medical insurance costs. Check out my video on this topic for the complete video explanation.
Implements linear regression on tabular insurance data to predict charges based on demographic and health features (age, BMI, smoking status, region). The model uses scikit-learn for training and evaluation, with the Kaggle insurance dataset preprocessed to handle categorical variables through encoding. Includes performance metrics and visualization of predictions versus actual values to assess model fit.
No commits in the last 6 months.
Stars
8
Forks
3
Language
Jupyter Notebook
License
—
Category
Last pushed
Jun 14, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/roshancyriacmathew/Medical-insurance-cost-prediction-using-linear-regression"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Ambarish-224/End-to-End-Insurance-Premium-Prediction
Insurance Premium Prediction is an Machine Learning Project which predicts Insurance premium...
KhanNosheen/Medical_Insurance_Cost_Prediction
Predicting medical insurance costs using Python and OLS Regression. Includes log transformation...
JensBender/medical-cost-prediction
🏥 An AI-powered application to predict out-of-pocket healthcare costs for personalized financial...
viochris/Stuntify-API
The high-performance backend engine for Stuntify. Built with FastAPI and Scikit-Learn to serve...
Chrisimana/biaya-kesehatan-prediction-using-neural-networks
Portofolio | Machine Learning | Project FreeCodeCamp