An effective variant of the Hartigan k-means algorithm
Not on the map. Why?
Abstract (arXiv)
The k-means problem is perhaps the classical clustering problem and often synonymous with Lloyd's algorithm (1957). It has become clear that Hartigan's algorithm (1975) gives better results in almost all cases, Telgarsky-Vattani note a typical improvement of 5% -- 10%. We point out that a very minor variation of Hartigan's method leads to another 2% -- 5% improvement; the improvement tends to become larger when either dimension or k increase.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 1 of its 21 references that are in the map. First posted on arXiv 23 Apr 2026.
Builds on
1 of 21 references.
References · 1
Built on by
Not cited yet.