c2c: Compare Two Classifications or Clustering Solutions of Varying Structure

Compare two classifications or clustering solutions that may or may not have the same number of classes, and that might have hard or soft (fuzzy, probabilistic) membership. Calculate various metrics to assess how the clusters compare to each other. The calculations are simple, but provide a handy tool for users unfamiliar with matrix multiplication. This package is not geared towards traditional accuracy assessment for classification/ mapping applications - the motivating use case is for comparing a probabilistic clustering solution to a set of reference or existing class labels that could have any number of classes (that is, without having to degrade the probabilistic clustering to hard classes).

Version:	0.1.0
Depends:	R (≥ 3.1.0)
Suggests:	testthat, knitr, rmarkdown, e1071
Published:	2017-07-23
DOI:	10.32614/CRAN.package.c2c
Author:	Mitchell Lyons [aut, cre]
Maintainer:	Mitchell Lyons <mitchell.lyons at gmail.com>
BugReports:	https://github.com/mitchest/c2c/issues
License:	GPL-3
URL:	https://github.com/mitchest/c2c/
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	c2c results

Documentation:

Reference manual:	c2c.pdf
Vignettes:	c2c workflow

Downloads:

Package source:	c2c_0.1.0.tar.gz
Windows binaries:	r-devel: c2c_0.1.0.zip, r-release: c2c_0.1.0.zip, r-oldrel: c2c_0.1.0.zip
macOS binaries:	r-release (arm64): c2c_0.1.0.tgz, r-oldrel (arm64): c2c_0.1.0.tgz, r-release (x86_64): c2c_0.1.0.tgz, r-oldrel (x86_64): c2c_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=c2c to link to this page.