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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.pdf |
| Vignettes: |
ksharp vignette |
| 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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.