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
Author:	David Charles Howe [aut, cre]
Maintainer:	David Charles Howe <kmodR at edgecondition.com>
License:	GPL-3
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	kmodR results

Documentation:

Reference manual:

kmodR.pdf

Downloads:

Package source:	kmodR_0.2.0.tar.gz
Windows binaries:	r-devel: kmodR_0.2.0.zip, r-release: kmodR_0.2.0.zip, r-oldrel: kmodR_0.2.0.zip
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

Linking:

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