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It provides functions that calculate Mahalanobis distance, Euclidean distance, Manhattan distance and Chebyshev distance between each pair of species in a list of data frames. These metrics are fundamental in various fields, such as cluster analysis, classification, and other applications of machine learning and data mining, where assessing similarity or dissimilarity between data is crucial. The package is designed to be flexible and easily integrated into data analysis workflows, providing reliable tools for evaluating distances in multidimensional contexts.
| Version: | 0.3.0 |
| Imports: | stats, ggplot2, reshape2 |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2024-05-20 |
| DOI: | 10.32614/CRAN.package.cmahalanobis |
| Author: | Flavio Gioia |
| Maintainer: | Flavio Gioia <flaviogioia.fg at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | cmahalanobis results |
| Reference manual: | cmahalanobis.pdf |
| Vignettes: |
my-vignette3 |
| Package source: | cmahalanobis_0.3.0.tar.gz |
| Windows binaries: | r-devel: cmahalanobis_0.3.0.zip, r-release: cmahalanobis_0.3.0.zip, r-oldrel: cmahalanobis_0.3.0.zip |
| macOS binaries: | r-release (arm64): cmahalanobis_0.3.0.tgz, r-oldrel (arm64): cmahalanobis_0.3.0.tgz, r-release (x86_64): cmahalanobis_0.3.0.tgz, r-oldrel (x86_64): cmahalanobis_0.3.0.tgz |
| Old sources: | cmahalanobis 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.