Package: kmodR 0.2.0

David Charles Howe

kmodR: K-Means with Simultaneous Outlier Detection

An implementation of the 'k-means--' algorithm proposed by Chawla and Gionis, 2013 in their paper, "k-means-- : A unified approach to clustering and outlier detection. SIAM International Conference on Data Mining (SDM13)", <doi:10.1137/1.9781611972832.21> and using 'ordering' described by Howe, 2013 in the thesis, Clustering and anomaly detection in tropical cyclones". Useful for creating (potentially) tighter clusters than standard k-means and simultaneously finding outliers inexpensively in multidimensional space.

Authors:David Charles Howe [aut, cre]

kmodR_0.2.0.tar.gz
kmodR_0.2.0.tar.gz(r-4.7-any)kmodR_0.2.0.tar.gz(r-4.6-any)
kmodR_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
kmodR/json (API)
NEWS

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 7 scripts 168 downloads 1 exports 0 dependencies

Last updated from:e57aa95e5a. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK90
source / vignettesOK173
linux-release-x86_64OK108
wasm-releaseOK90

Exports:kmod

Dependencies: