Performance of a K-Means Algorithm Driven by Careful Seeding

Libero Nigro, Franco Cicirelli

2023

Abstract

This paper proposes a variation of the K-Means clustering algorithm, named Population-Based K-Means (PB-K-MEANS), which founds its behaviour on careful seeding. The new K-Means algorithm rests on a greedy version of the K-Means++ seeding procedure (g_kmeans++), which proves effective in the search for an accurate clustering solution. PB-K-MEANS first builds a population of candidate solutions by independent runs of K-Means with g_kmeans++. Then the reservoir is used for recombining the stored solutions by Repeated K-Means toward the attainment of a final solution which minimizes the distortion index. PB-K-MEANS is currently implemented in Java through parallel streams and lambda expressions. The paper first recalls basic concepts of clustering and of K-Means together with the role of the seeding procedure, then it goes on by describing basic design and implementation issues of PB-K-MEANS. After that, simulation experiments carried out both on synthetic and real-world datasets are reported, confirming good execution performance and careful clustering.

Paper Citation

in Harvard Style

Nigro L. and Cicirelli F. (2023). Performance of a K-Means Algorithm Driven by Careful Seeding. In Proceedings of the 13th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH; ISBN 978-989-758-668-2, SciTePress, pages 27-36. DOI: 10.5220/0012045000003546

in Bibtex Style

@conference{simultech23,
author={Libero Nigro and Franco Cicirelli},
title={Performance of a K-Means Algorithm Driven by Careful Seeding},
booktitle={Proceedings of the 13th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH},
year={2023},
pages={27-36},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012045000003546},
isbn={978-989-758-668-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH
TI - Performance of a K-Means Algorithm Driven by Careful Seeding
SN - 978-989-758-668-2
AU - Nigro L.
AU - Cicirelli F.
PY - 2023
SP - 27
EP - 36
DO - 10.5220/0012045000003546
PB - SciTePress