A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System

Zhenni Jiang, Xiyu Liu and Minghe Sun

Mathematical Problems in Engineering, 2019, vol. 2019, 1-13

Abstract:

This study proposes a novel method to calculate the density of the data points based on K-nearest neighbors and Shannon entropy. A variant of tissue-like P systems with active membranes is introduced to realize the clustering process. The new variant of tissue-like P systems can improve the efficiency of the algorithm and reduce the computation complexity. Finally, experimental results on synthetic and real-world datasets show that the new method is more effective than the other state-of-the-art clustering methods.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1713801

DOI: 10.1155/2019/1713801

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