Community Clustering Merge is a Python library designed to seamlessly merge the results of multiple clustering algorithms into a unified community structure. Leveraging the efficiency of the Union-Find (Disjoint Set) data structure, this tool ensures accurate and optimized merging of overlapping and intertwined clusters, while effectively handling edge cases such as invalid cluster identifiers.
- Efficient Merging: Utilizes the Union-Find algorithm for optimal performance during merging operations.
- Handling Invalid Clusters: Properly manages entities not assigned to any cluster across all clustering results (e.g., cluster ID
0). - Minimal Cluster ID Assignment: Assigns the smallest valid cluster ID within merged groups for consistency.
- Scalable: Suitable for large-scale datasets with multiple clustering results.
- Easy Integration: Simple API for integrating with existing data pipelines.
- Comprehensive Testing: Includes extensive test cases covering simple, complex, and edge scenarios.
- Customizable: Easily extendable to incorporate additional merging strategies.
This project is licensed under the MIT License.
For any questions or suggestions, feel free to open an issue or contact the maintainer:
- Email: [email protected]
- GitHub: @MissArtemis
- Inspired by the need for efficient and accurate merging of clustering results.
- Thanks to the open-source community for their invaluable contributions and support.