Obesity Data Using Decision Tree Algorithm

📘 Overview

This project analyzes obesity-related data to classify individuals based on lifestyle and physical characteristics using a Decision Tree Algorithm.

📊 Dataset

The dataset Obesity.csv contains details such as age, gender, eating habits, and activity levels.

🧠 Algorithm Used

• Decision Tree Classifier

⚙️ Steps Involved

1. Load and explore the dataset.
2. Encode categorical variables.
3. Train a Decision Tree model.
4. Evaluate model performance and visualize decision paths.

🧾 Results

The model helps in predicting obesity levels based on behavior and health-related features.

🛠️ Tools Used

• Python
• Pandas
• Scikit-learn
• Matplotlib