White Box Cluster Algorithm Design allows you to create Representative based cluster algorithm by using reusable components. This way one can recreate already available cluster algorithms (i.e. K-Means, K-Means++, PAM) but also create new cluster algorithms not available in the literature or any other software. For more information see papers <doi:10.1007/s10462-009-9133-6> and <doi:10.1016/j.datak.2012.03.005>.
| Version: | 0.1.2 |
| Depends: | graphics, stats, clusterCrit, cluster |
| Suggests: | methods, testthat |
| Published: | 2018-11-20 |
| Author: | Sandro Radovanovic, Milan Vukicevic |
| Maintainer: | Sandro Radovanovic <sandro.radovanovic at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | whiboclustering results |
| Reference manual: | whiboclustering.pdf |
| Package source: | whiboclustering_0.1.2.tar.gz |
| Windows binaries: | r-devel: whiboclustering_0.1.2.zip, r-release: whiboclustering_0.1.2.zip, r-oldrel: whiboclustering_0.1.2.zip |
| OS X binaries: | r-release: whiboclustering_0.1.2.tgz, r-oldrel: whiboclustering_0.1.2.tgz |
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