Package: SoftClustering 2.1.3

G. Peters

SoftClustering: Soft Clustering Algorithms

It contains soft clustering algorithms, in particular approaches derived from rough set theory: Lingras & West original rough k-means, Peters' refined rough k-means, and PI rough k-means. It also contains classic k-means and a corresponding illustrative demo.

Authors:G. Peters

SoftClustering_2.1.3.tar.gz
SoftClustering_2.1.3.zip(r-4.7-any)SoftClustering_2.1.3.zip(r-4.6-any)
SoftClustering_2.1.3.tar.gz(r-4.7-any)SoftClustering_2.1.3.tar.gz(r-4.6-any)
SoftClustering_2.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SoftClustering/json (API)

# Install 'SoftClustering' in R:

install.packages('SoftClustering', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

DemoDataC2D2a - A small two-dimensional dataset with two clusters for demonstration purposes. See examples in the Help/Description of a function, e.g. for HardKMeansDemo().
initMeansC2D2a - Two-dimensional dataset with two initial cluster means for the dataset DemoDataC2D2a. See examples in the Help/Description of a function, e.g. for HardKMeansDemo().
initMeansC3D2a - Two-dimensional dataset with three initial cluster means for the dataset DemoDataC2D2a. See examples in the Help/Description of a function, e.g. for HardKMeansDemo().
initMeansC4D2a - Two-dimensional dataset with four initial cluster means for the dataset DemoDataC2D2a. See examples in the Help/Description of a function, e.g. for HardKMeansDemo().
initMeansC5D2a - Two-dimensional dataset with five initial cluster means for the dataset DemoDataC2D2a. See examples in the Help/Description of a function, e.g. for HardKMeansDemo().

On CRAN:

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

1.11 score 13 scripts 203 downloads 8 exports 0 dependencies

Last updated from:a1c58da02d. Checks:6 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	107
source / vignettes	OK	149
linux-release	OK	96
windows-devel	OK	63
windows-release	OK	48
wasm-release	OK	91

Exports:createLowerMShipMatrix HardKMeans HardKMeansDemo normalizeMatrix RoughKMeans_LW RoughKMeans_PE RoughKMeans_PI RoughKMeans_SHELL

Dependencies:

Citation

Readme and manuals

Help Manual

Help page	Topics
Create Lower Approximation	createLowerMShipMatrix
Rough k-Means Plotting	datatypeInteger
A small two-dimensional dataset with two clusters for demonstration purposes. See examples in the Help/Description of a function, e.g. for HardKMeansDemo().	DemoDataC2D2a
Hard k-Means	HardKMeans
Hard k-Means Demo	HardKMeansDemo
Initialize Means Matrix	initializeMeansMatrix
Two-dimensional dataset with two initial cluster means for the dataset DemoDataC2D2a. See examples in the Help/Description of a function, e.g. for HardKMeansDemo().	initMeansC2D2a
Two-dimensional dataset with three initial cluster means for the dataset DemoDataC2D2a. See examples in the Help/Description of a function, e.g. for HardKMeansDemo().	initMeansC3D2a
Two-dimensional dataset with four initial cluster means for the dataset DemoDataC2D2a. See examples in the Help/Description of a function, e.g. for HardKMeansDemo().	initMeansC4D2a
Two-dimensional dataset with five initial cluster means for the dataset DemoDataC2D2a. See examples in the Help/Description of a function, e.g. for HardKMeansDemo().	initMeansC5D2a
Matrix Normalization	normalizeMatrix
Rough k-Means Plotting	plotRoughKMeans
Lingras & West's Rough k-Means	RoughKMeans_LW
Peters' Rough k-Means	RoughKMeans_PE
'PI' Rough k-Means	RoughKMeans_PI
Rough k-Means Shell	RoughKMeans_SHELL

Package: SoftClustering 2.1.3

SoftClustering: Soft Clustering Algorithms

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)