The R Journal: article published in 2011, volume 3:2

Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming
Haizhou Wang and Mingzhou Song , The R Journal (2011) 3:2, pages 29-33.

Abstract The heuristic k-means algorithm, widely used for cluster analysis, does not guarantee optimality. We developed a dynamic programming algorithm for optimal one-dimensional clustering. The algorithm is implemented as an R package called Ckmeans.1d.dp. We demonstrate its advantage in optimality and runtime over the standard iterative k-means algorithm.

CRAN packages: Ckmeans.1d.dp

This article is licensed under a Creative Commons Attribution 3.0 Unported license.

@article{RJ-2011-015,
  author = {Haizhou Wang and Mingzhou Song},
  title = {{Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension
          by Dynamic Programming}},
  year = {2011},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2011-015},
  url = {https://doi.org/10.32614/RJ-2011-015},
  pages = {29--33},
  volume = {3},
  number = {2}
}