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The Patient Rule Induction Method (PRIM) is typically used for "bump hunting" data mining to identify regions with abnormally high concentrations of data with large or small values. This package extends this methodology so that it can be applied to binary classification problems and used for prediction.
| Version: | 2.0.0 |
| Depends: | R (≥ 3.1.1), stats, prim (≥ 1.0.16) |
| Suggests: | kernlab, testthat |
| Published: | 2016-10-01 |
| DOI: | 10.32614/CRAN.package.supervisedPRIM |
| Author: | David Shaub [aut, cre] |
| Maintainer: | David Shaub <davidshaub at gmx.com> |
| BugReports: | https://github.com/dashaub/supervisedPRIM/issues |
| License: | GPL-3 |
| URL: | https://github.com/dashaub/supervisedPRIM |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | supervisedPRIM results |
| Reference manual: | supervisedPRIM.pdf |
| Package source: | supervisedPRIM_2.0.0.tar.gz |
| Windows binaries: | r-devel: supervisedPRIM_2.0.0.zip, r-release: supervisedPRIM_2.0.0.zip, r-oldrel: supervisedPRIM_2.0.0.zip |
| macOS binaries: | r-release (arm64): supervisedPRIM_2.0.0.tgz, r-oldrel (arm64): supervisedPRIM_2.0.0.tgz, r-release (x86_64): supervisedPRIM_2.0.0.tgz, r-oldrel (x86_64): supervisedPRIM_2.0.0.tgz |
| Old sources: | supervisedPRIM 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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