SujanNeupane42 / Medical-Insurance-Cost-Prediction

In this regression project, We will make use of different features like age, BMI, region, sex, smoker, etc to predict the medical insurance cost for an individual.

Medical-Insurance-Cost-Prediction

This is a simple regression project. I have used following python libraries: numpy, matplotlib, seaborn, and sklearn.

I have used the following Models:

1. KNeighborsRegressor
2. LinearRegression
3. XGBRegressor
4. DescisonTreeRegressor
5. RandomForestRegressor

Furthermore, I have performed Hyperparameter tuning for these models as well to optimize the performance of these models on validation and testing set and reduce loss function.

Dataset

I have not included the dataset in the repository. However, you could find the official dataset on Kaggle

In this regression project, We will make use of different features like age, BMI, region, sex, smoker, etc to predict the medical insurance cost for an individual.