Package: ksharp 0.1.0.1

ksharp: Cluster Sharpening

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.

Authors:Tomasz Konopka [aut, cre]

ksharp_0.1.0.1.tar.gz
ksharp_0.1.0.1.zip(r-4.5)ksharp_0.1.0.1.zip(r-4.4)ksharp_0.1.0.1.zip(r-4.3)
ksharp_0.1.0.1.tgz(r-4.4-any)ksharp_0.1.0.1.tgz(r-4.3-any)
ksharp_0.1.0.1.tar.gz(r-4.5-noble)ksharp_0.1.0.1.tar.gz(r-4.4-noble)
ksharp_0.1.0.1.tgz(r-4.4-emscripten)ksharp_0.1.0.1.tgz(r-4.3-emscripten)
ksharp.pdf |ksharp.html
ksharp/json (API)

# Install 'ksharp' in R:
install.packages('ksharp', repos = c('https://tkonopka.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tkonopka/ksharp/issues

Datasets:

    On CRAN:

    4 exports 3 stars 0.92 score 0 dependencies 4 scripts 127 downloads

    Last updated 3 years agofrom:dc612691c4. Checks:OK: 1 WARNING: 6. Indexed: yes.

    TargetResultDate
    Doc / VignettesOKSep 04 2024
    R-4.5-winWARNINGSep 04 2024
    R-4.5-linuxWARNINGSep 04 2024
    R-4.4-winWARNINGSep 04 2024
    R-4.4-macWARNINGSep 04 2024
    R-4.3-winWARNINGSep 04 2024
    R-4.3-macWARNINGSep 04 2024

    Exports:ksharpmedinfoneiinfosilinfo

    Dependencies:

    Cluster sharpening using ksharp

    Rendered fromksharp.Rmdusingknitr::rmarkdownon Sep 04 2024.

    Last update: 2020-01-18
    Started: 2018-03-01