kmed

Distance-Based k-Medoids

A simple and fast distance-based k-medoids clustering algorithm from Park and Jun (2009) <doi:10.1016/j.eswa.2008.01.039>. Calculate distances for mixed variable data such as Gower (1971) <doi:10.2307/2528823>, Wishart (2003) <doi:10.1007/978-3-642-55721-7_23>, Podani (1999) <doi:10.2307/1224438>, Huang (1997) <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.94.9984&rep=rep1&type=pdf>, and Harikumar and PV (2015) <doi:10.1016/j.procs.2015.10.077>. Cluster validation applies bootstrap procedure producing a heatmap with a flexible reordering matrix algorithm such as complete, ward, or average linkages.

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Description file content

Package
kmed
Type
Package
Title
Distance-Based k-Medoids
Version
0.0.1
Date
2018-02-09
Author
Weksi Budiaji
Maintainer
Weksi Budiaji
Description
A simple and fast distance-based k-medoids clustering algorithm from Park and Jun (2009) . Calculate distances for mixed variable data such as Gower (1971) , Wishart (2003) , Podani (1999) , Huang (1997) , and Harikumar and PV (2015) . Cluster validation applies bootstrap procedure producing a heatmap with a flexible reordering matrix algorithm such as complete, ward, or average linkages.
Depends
R (>= 2.10)
License
GPL-3
LazyData
TRUE
RoxygenNote
6.0.1
Suggests
knitr, rmarkdown
VignetteBuilder
knitr
Imports
ggplot2
NeedsCompilation
no
Packaged
2018-02-09 19:51:10 UTC; Weksi
Repository
CRAN
Date/Publication
2018-02-12 10:12:53 UTC

install.packages('kmed')

0.0.1

10 days ago

Weksi Budiaji

GPL-3

Depends on

R (>= 2.10)

Imports

ggplot2

Suggests

knitr, rmarkdown

Discussions