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.html , optimus.pdf |
| Vignettes: |
Optimus workflow (source, R code) |
| 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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