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arXiv · 1702.04739

An Efficient Parallel Data Clustering Algorithm Using Isoperimetric Number of Trees

Ramin Javadi·Saleh Ashkboos
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Abstract

We propose a parallel graph-based data clustering algorithm using CUDA GPU, based on exact clustering of the minimum spanning tree in terms of a minimum isoperimetric criteria. We also provide a comparative performance analysis of our algorithm with other related ones which demonstrates the general superiority of this parallel algorithm over other competing algorithms in terms of accuracy and speed.

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Ramin Javadi, Saleh Ashkboos. 2017-02-15. An Efficient Parallel Data Clustering Algorithm Using Isoperimetric Number of Trees. https://arxiv.org/abs/1702.04739

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