Accelerating the k-Means++ Algorithm by Using Geometric Information

Clustering is a fundamental task in data analysis with applications across a wide range of fields, such as computer vision, pattern recognition, and data mining. Real-world use cases include social network analysis, medical imaging, market segmentation, and anomaly detection, to name a few. In this...

Celý popis

Podrobná bibliografia

Vydané v:	IEEE access Ročník 13; s. 67693 - 67717
Hlavní autori:	Rodriguez Corominas, Guillem, Blesa, Maria J., Blum, Christian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 2025
Predmet:	Approximation algorithms Clustering Clustering algorithms Computational efficiency D² sampling Filters k-means Machine learning algorithms Measurement norm Prediction algorithms Scalability triangle inequality Vectors
ISSN:	2169-3536, 2169-3536
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!