用网格和密度峰修改FCM

Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI:10.1145/3357777.3357783

Renxia Wan, Weiqi Wang

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摘要

本文利用网格和密度峰对FCM算法进行了改进。采用混合网格技术的密度峰聚类算法确定FCM的初始聚类位置。我们还使用聚类核代替聚类质心，使得改进后的算法可以有效地发现任意形状的聚类。实验结果表明，该算法的性能优于原有算法。

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Modifying FCM with grids and density peaks

In this paper, we modify the FCM algorithm with grids and density peaks. We apply the density peak clustering algorithm mixed with grid technology to determine the initial clustering positions of FCM. We also use cluster cores instead of cluster centroids, so that the modified algorithm can effectively discover arbitrary shape clusters. Experimental results show that the performance of the proposed algorithm is found to be superior to its ECTs.

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Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence

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