A hybrid clustering method based on k-means algorithm

Hongwei Chen

doi:10.1117/12.2653161

20 October 2022 A hybrid clustering method based on k-means algorithm

Hongwei Chen

Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 123502D (2022) https://doi.org/10.1117/12.2653161
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China

Abstract

We propose a novel hybrid algorithm that effectively combines K-means clustering and hierarchical and uses triangle inequality to accelerate the clustering speed. The HTK clustering algorithm can produce the same results as the standard K-means clustering algorithm. The proposed algorithm is superior to the standard K-means clustering algorithm in terms of running time and memory usage, thus improving the clustering speed and time complexity of the algorithm. The proposed clustering methods are tested on sci-kit learn datasets, and they are more favorable than the random restart K-means algorithm.

Citation Download Citation

Hongwei Chen "A hybrid clustering method based on k-means algorithm", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 123502D (20 October 2022); https://doi.org/10.1117/12.2653161

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