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.

Version: 0.2.0
Suggests: testthat
Published: 2022-05-12
DOI: 10.32614/CRAN.package.kmodR
Author: David Charles Howe ORCID iD [aut, cre]
Maintainer: David Charles Howe <kmodR at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: kmodR results


Reference manual: kmodR.pdf


Package source: kmodR_0.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): kmodR_0.2.0.tgz, r-oldrel (arm64): kmodR_0.2.0.tgz, r-release (x86_64): kmodR_0.2.0.tgz, r-oldrel (x86_64): kmodR_0.2.0.tgz
Old sources: kmodR archive


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