🌳 Decision Tree Classification – Diabetes Prediction

This project builds a Decision Tree model to predict diabetes outcomes based on patient health data.

📊 Project Goals

• Analyze relationships between health features and diabetes outcome
• Build a classification model using Decision Tree
• Identify the most important features affecting predictions

🧠 Methods & Model

• Exploratory Data Analysis (EDA)
• Decision Tree Classifier (scikit-learn)
• Feature Importance Analysis

🛠️ Tech Stack

• Python (pandas, numpy, scikit-learn)
• Data Visualization (matplotlib, seaborn)

📁 Dataset

• Diabetes dataset (Pima Indians Diabetes dataset)

📈 Key Insights

• Glucose level is the most important factor influencing diabetes prediction
• BMI and Age also significantly impact the model
• Some features (e.g., SkinThickness, Insulin) have lower importance
• Decision Tree provides interpretable results for feature impact

🚀 How to Run

pip install -r requirements.txt