This package implements a dynamic programming algorithm to perform optimal one-dimensional k-means clustering, by minimizing the sum of squares of within-cluster distances. As an alternative to the standard heuristic k-means algorithm, this algorithm guarantees optimality and repeatability.
| Version: | 3.02 |
| Depends: | R (≥ 2.10.0) |
| Published: | 2014-03-30 |
| Author: | Joe Song and Haizhou Wang |
| Maintainer: | Joe Song <joemsong at cs.nmsu.edu> |
| License: | LGPL (≥ 3) |
| NeedsCompilation: | yes |
| Citation: | Ckmeans.1d.dp citation info |
| CRAN checks: | Ckmeans.1d.dp results |
| Reference manual: | Ckmeans.1d.dp.pdf |
| Package source: | Ckmeans.1d.dp_3.02.tar.gz |
| Windows binaries: | r-devel: Ckmeans.1d.dp_3.02.zip, r-release: Ckmeans.1d.dp_3.02.zip, r-oldrel: Ckmeans.1d.dp_3.02.zip |
| OS X Snow Leopard binaries: | r-release: Ckmeans.1d.dp_3.02.tgz, r-oldrel: Ckmeans.1d.dp_3.02.tgz |
| OS X Mavericks binaries: | r-release: Ckmeans.1d.dp_3.02.tgz |
| Old sources: | Ckmeans.1d.dp archive |
| Reverse imports: | opm |