PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration

Hongfei Wu; Yancheng Yuan

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arXiv · 2501.15964

PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration

Hongfei Wu·Yancheng Yuan

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Abstract

Convex clustering is a popular clustering model without requiring the number of clusters as prior knowledge. It can generate a clustering path by continuously solving the model with a sequence of regularization parameter values. This paper introduces {\it PyClustrPath}, a highly efficient Python package for solving the convex clustering model with GPU acceleration. {\it PyClustrPath} implements popular first-order and second-order algorithms with a clean modular design. Such a design makes {\it PyClustrPath} more scalable to incorporate new algorithms for solving the convex clustering model in the future. We extensively test the numerical performance of {\it PyClustrPath} on popular clustering datasets, demonstrating its superior performance compared to the existing solvers for generating the clustering path based on the convex clustering model. The implementation of {\it PyClustrPath} can be found at: https://github.com/D3IntOpt/PyClustrPath.

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BibTeX RIS

Hongfei Wu, Yancheng Yuan. 2025-01-27. PyClustrPath: An efficient Python package for generating clustering paths with GPU acceleration. https://arxiv.org/abs/2501.15964

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