An R package for assessment and diagnostics of 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 such that it increases 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. More details on the background and theory behind using predictive models for classification assessment, in an ecological context, can be found in Lyons et al. (2016).
In R, simply use
See the package page on CRAN for more details: https://cran.r-project.org/package=optimus
If you want to install the development version of optimus, for example if I've added something new that you want to use, but it's not yet up on CRAN, then you can also install directly from github. It's very easy - simply use Hadley Wickham's (excellent) devtools package - install devtools from CRAN within R using
There are some probably. If you find them, please let me know about them - either directly on github, or the contact details below.
You can find the vignette on the CRAN home page, or you can access it here too (might be new things here before CRAN occasionally). Check out the tutorial here.
Lyons et al. 2016. Model-based assessment of ecological community classifications. Journal of Vegetation Science: 27 (4) 704--715. DOI: http://dx.doi.org/10.1111/jvs.12400
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