This project involves building a 🌲 regression tree model to predict medical costs based on various features provided in the Medical Cost Personal Dataset. The goal is to understand the relationship between different factors and the medical costs incurred by individuals.

The dataset used in this project is the Medical Cost Personal Dataset. It contains information about individuals, including age, gender, BMI, smoking status, region, and medical costs.

• age: Age of the individual.
• sex: Gender of the individual (male or female).
• bmi: Body Mass Index (BMI) of the individual.
• children: Number of children/dependents covered by health insurance.
• smoker: Smoking status of the individual (yes or no)..
• region: Region..
• charges: Medical costs incurred by the individual (target variable).