Speeding up k-means clustering in high dimensions by pruning unnecessary distance computations

Haowen Zhang, Jing Li, Junru Zhang, Yabo Dong

Abstract: Highlights•A new framework named LBKC is proposed for accelerating k-means clustering.•Three carefully designed lower bounds are presented and embedded into LBKC.•LBKC can be combined with the state-of-the-art to improve their performance.•We conduct extensive experiments to validate the effectiveness of the proposals.