kmodR: K-Means with Simultaneous Outlier Detection
Version 0.1.0

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)", 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.

AuthorDavid Charles Howe [aut, cre]
Date of publication2015-03-26 10:51:13
MaintainerDavid Charles Howe <kmodR@edgecondition.com>
LicenseGPL-3
Version0.1.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("kmodR")

Getting started

README.md

Popular man pages

kmod: K-Means clustering with simultaneous Outlier Detection
See all...

All man pages Function index File listing

Man pages

kmod: K-Means clustering with simultaneous Outlier Detection

Functions

C_zero Source code
Q_reorder Source code
converged Source code
delta_C Source code
dist_sqr_XC Source code
dist_sqr_xC Source code
get_C_sizes Source code
get_Ci Source code
get_c Source code
get_extra_centroid_index Source code
get_extra_centroids Source code
get_within_cluster_ss Source code
kmod Man page Source code
kmod_summary Source code
sum_dist_squares Source code

Files

tests
tests/testthat.R
tests/testthat
tests/testthat/test_kmodR.R
NAMESPACE
R
R/kmod.R
README.md
MD5
DESCRIPTION
man
man/kmod.Rd
kmodR documentation built on May 20, 2017, 3:56 a.m.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs in the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.