Index Quality Analysis 📊🔍

Welcome to the Index Quality Analysis repository! This project explores the performance of FAISS and Annoy indexing algorithms with various metrics to compare search quality.

🚀 Features

• Index Comparison: Compares the performance of FAISS and Annoy indexes using different distance metrics.
• Quality Metrics: Evaluates search quality using MAP@20, DCG@20, MRR, and ERR metrics.
• Data-Driven Insights: Provides a detailed analysis of the results to help choose the best indexing strategy for different scenarios.

📈 Results

The following table summarizes the search quality results for each index:

Index Type	MAP@20	DCG@20	MRR	ERR
faiss_L2	0.519605	3.139235	0.461988	0.144568
faiss_IP	0.745815	3.419188	0.708333	0.336610
annoy_angular	0.533772	3.057684	0.461988	0.156234
annoy_euclidean	0.526550	3.147764	0.461988	0.145956
annoy_manhattan	0.243591	1.513743	0.195767	0.101152

🛠️ Getting Started

To get started with the Index Quality Analysis project, follow these steps:

1. Clone the Repository:

   git clone https://github.com/ivanovsdesign/index_quality.git
   

2. Navigate to the Project Directory:

   cd index_quality

3. Explore the Analysis:

   • Review the code and documentation to understand how the indexes were created and evaluated.

   • Analyze the results to gain insights into the performance of each indexing method.

🤝 Contributing

Contributions are welcome! Please read the CONTRIBUTING.md for details on how to contribute to this project.

📄 License

This project is licensed under the MIT License.

📬 Contact

For questions or feedback, please open an issue on GitHub.

🌟 Thank you for visiting the repository! If you find this project helpful, please consider starring it to show your support. Happy coding! 🚀