ECA-CE: An Evolutionary Clustering Algorithm with Initial Population by Clustering Ensemble

Chao Xu, Chunlin Xu, Shengli Wu

2023

Abstract

Evolutionary clustering is a type of algorithm that uses genetic algorithms to optimize clustering results. Unlike traditional clustering algorithms which obtain clustering results by iteratively increasing the distance between clusters and reducing the distance between instances within a cluster, the evolutionary clustering algorithm tries to search for the optimal clustering result in the solution space. Not surprisingly, the initial population set in an evolutionary clustering algorithm has significant influence on the final results. To ensure the quality of the initial population, this paper proposed a clustering ensemble-based method, ECA-CE, to do the initial population for the evolutionary clustering algorithm. In ECA-CE, a clustering ensemble method, Hybrid Bipartite Graph Formulation, is applied. Extensive experiments are conducted on 20 benchmark datasets, and the experimental results demonstrate that the proposed ECA-CE is more effective than two evolutionary clustering algorithms F1-ECAC and ECAC in terms of Adjusted Rand index.

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Paper Citation


in Harvard Style

Xu C., Xu C. and Wu S. (2023). ECA-CE: An Evolutionary Clustering Algorithm with Initial Population by Clustering Ensemble. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 132-139. DOI: 10.5220/0011621700003393


in Bibtex Style

@conference{icaart23,
author={Chao Xu and Chunlin Xu and Shengli Wu},
title={ECA-CE: An Evolutionary Clustering Algorithm with Initial Population by Clustering Ensemble},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={132-139},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011621700003393},
isbn={978-989-758-623-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - ECA-CE: An Evolutionary Clustering Algorithm with Initial Population by Clustering Ensemble
SN - 978-989-758-623-1
AU - Xu C.
AU - Xu C.
AU - Wu S.
PY - 2023
SP - 132
EP - 139
DO - 10.5220/0011621700003393