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Assessment and diagnostics for comparing competing clustering solutions, using predictive models. The main intended use is for comparing clustering/classification solutions of ecological data (e.g. presence/absence, counts, ordinal scores) to 1) find an optimal partitioning solution, 2) identify characteristic species and 3) refine a classification by merging clusters that increase predictive performance. However, in a more general sense, this package can do the above for any set of clustering solutions for i observations of j variables.
Version: | 0.2.0 |
Depends: | R (≥ 3.1.0) |
Imports: | stats, methods, mvabund (≥ 3.1), ordinal (≥ 2015.1-21) |
Suggests: | testthat, knitr, rmarkdown |
Published: | 2018-01-16 |
DOI: | 10.32614/CRAN.package.optimus |
Author: | Mitchell Lyons [aut, cre] |
Maintainer: | Mitchell Lyons <mitchell.lyons at gmail.com> |
BugReports: | https://github.com/mitchest/optimus/issues |
License: | GPL-3 |
URL: | https://github.com/mitchest/optimus/ |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | optimus results |
Reference manual: | optimus.pdf |
Vignettes: |
Optimus workflow |
Package source: | optimus_0.2.0.tar.gz |
Windows binaries: | r-devel: optimus_0.2.0.zip, r-release: optimus_0.2.0.zip, r-oldrel: optimus_0.2.0.zip |
macOS binaries: | r-release (arm64): optimus_0.2.0.tgz, r-oldrel (arm64): optimus_0.2.0.tgz, r-release (x86_64): optimus_0.2.0.tgz, r-oldrel (x86_64): optimus_0.2.0.tgz |
Old sources: | optimus archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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