{"id":26184543,"url":"https://github.com/sergeyklay/clusterium","last_synced_at":"2025-12-25T02:08:10.436Z","repository":{"id":281340545,"uuid":"944974028","full_name":"sergeyklay/clusterium","owner":"sergeyklay","description":"QA Dataset Toolkit for clustering and 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Clusterium\n\n[![CI](https://github.com/sergeyklay/clusterium/actions/workflows/ci.yml/badge.svg)](https://github.com/sergeyklay/clusterium/actions/workflows/ci.yml)\n[![codecov](https://codecov.io/gh/sergeyklay/clusterium/graph/badge.svg?token=T5d9KTXtqP)](https://codecov.io/gh/sergeyklay/clusterium)\n\nA toolkit for clustering, analyzing, and benchmarking text data using state-of-the-art embedding models and clustering algorithms.\n\n## Features\n\n- **Dirichlet Process Clustering**: Implements the Dirichlet Process for text clustering\n- **Pitman-Yor Process Clustering**: Implements the Pitman-Yor Process for text clustering with improved performance\n- **Evaluation**: Evaluates clustering results using a variety of metrics, including Silhouette Score, Davies-Bouldin Index, and Power-law Analysis\n- **Visualization**: Generates plots of cluster size distributions\n\n## Installation\n\nFor detailed installation instructions, please see [INSTALL.md](INSTALL.md).\n\n### Quick Start\n\n```bash\ngit clone https://github.com/sergeyklay/clusterium.git\ncd clusterium\npoetry install\n```\n\n## Usage\n\nFor detailed usage instructions, use cases, examples, and advanced configuration options, please see [USAGE.md](USAGE.md).\n\n### Quick Start\n\n```bash\n# Run clustering\nclusx --input your_data.csv --column your_column --output clusters.csv\n\n# Evaluate clustering results and generate visualizations\nclusx evaluate \\\n  --input input.csv \\\n  --column your_column \\\n  --dp-clusters output_dp.csv \\\n  --pyp-clusters output_pyp.csv \\\n  --plot\n```\n\n### Python API Example\n\n```python\nfrom clusx.clustering import DirichletProcess\nfrom clusx.clustering.utils import load_data_from_csv, save_clusters_to_json\n\n# Load data\ntexts, data = load_data_from_csv(\"your_data.csv\", column=\"your_column\")\n\n# Perform clustering\ndp = DirichletProcess(alpha=1.0)\nclusters, params = dp.fit(texts)\n\n# Save results\nsave_clusters_to_json(\"clusters.json\", texts, clusters, \"DP\", data)\n```\n\n## License\n\nThis project is licensed under the MIT License - see the LICENSE file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsergeyklay%2Fclusterium","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsergeyklay%2Fclusterium","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsergeyklay%2Fclusterium/lists"}