High-Performance Open-Source Archive
Clustering typically assigns data points into discrete groups, but the clusters can sometimes be indistinct. Cluster sharpening adjusts an existing clustering to create contrast between groups. This package provides a general interface for cluster sharpening along with several implementations based on different excision criteria.
| Version: | 0.1.0.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | methods, stats |
| Suggests: | cluster, dbscan, knitr, Rcssplot (≥ 1.0.0), rmarkdown, testthat |
| Published: | 2020-01-26 |
| DOI: | 10.32614/CRAN.package.ksharp |
| Author: | Tomasz Konopka [aut, cre] |
| Maintainer: | Tomasz Konopka <tokonopka at gmail.com> |
| BugReports: | https://github.com/tkonopka/ksharp/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/tkonopka/ksharp |
| NeedsCompilation: | no |
| CRAN checks: | ksharp results |
| Reference manual: | ksharp.html , ksharp.pdf |
| Vignettes: |
ksharp vignette (source, R code) |
| Package source: | ksharp_0.1.0.1.tar.gz |
| Windows binaries: | r-devel: ksharp_0.1.0.1.zip, r-release: ksharp_0.1.0.1.zip, r-oldrel: ksharp_0.1.0.1.zip |
| macOS binaries: | r-release (arm64): ksharp_0.1.0.1.tgz, r-oldrel (arm64): ksharp_0.1.0.1.tgz, r-release (x86_64): ksharp_0.1.0.1.tgz, r-oldrel (x86_64): ksharp_0.1.0.1.tgz |
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