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DiabetesPrediction

Predict diabetes outcomes using Naive Bayes classification.
This project analyzes patient data to predict whether a person is likely to have diabetes based on clinical features.


Features

  • Classification: Predicts diabetes risk (Yes/No) using Naive Bayes.
  • Handles dataset preprocessing, missing value handling, and feature scaling.
  • Supports exploratory data analysis and visualizations to understand key factors affecting diabetes.
  • Generates performance metrics like accuracy, confusion matrix, and classification report.

Installation / Setup

Requirements

  • Python 3.8+
  • Packages in requirements.txt (pandas, numpy, scikit-learn, matplotlib, seaborn, etc.)

Steps

# Clone the repository
git clone <your-repo-link>
cd DiabetesPrediction

# Create virtual environment
python -m venv venv
source venv/bin/activate       # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt