Optimal k-... The R Journal (original) (raw)

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

Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic ProgrammingPDF download
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

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@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} }