Facilitates optimal clustering of a data set. Provides a framework to run a wide range of clustering algorithms to determine the optimal number (k) of clusters in the data. Then analyzes the cluster assignments from each clustering algorithm to identify samples that repeatedly classify to the same group. We call these 'core clusters', providing a basis for later class discovery.
Version: | 1.1.0 |
Depends: | R (≥ 2.10), cluster, clValid, fpc |
Imports: | methods, grDevices, graphics, stats, utils |
Suggests: | RUnit, NMF, ConsensusClusterPlus, rgl, kohonen |
Published: | 2015-10-12 |
Author: | Albert Chen [aut, cre], Timothy E Sweeney [aut], Olivier Gevaert [ths] |
Maintainer: | Albert Chen <acc2015 at stanford.edu> |
License: | GPL-2 |
NeedsCompilation: | no |
Citation: | COMMUNAL citation info |
CRAN checks: | COMMUNAL results |
Reference manual: | COMMUNAL.pdf |
Vignettes: |
COMMUNAL: A Robust Method for Selection of Cluster Number K |
Package source: | COMMUNAL_1.1.0.tar.gz |
Windows binaries: | r-devel: COMMUNAL_1.1.0.zip, r-release: COMMUNAL_1.1.0.zip, r-oldrel: COMMUNAL_1.1.0.zip |
OS X Mavericks binaries: | r-release: COMMUNAL_1.1.0.tgz, r-oldrel: COMMUNAL_1.1.0.tgz |
Old sources: | COMMUNAL archive |
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