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Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
| Version: | 3.0.2 |
| Depends: | R (≥ 4.1) |
| Imports: | DT (≥ 0.27), pls (≥ 2.8-1), dplyr (≥ 1.1.0), shiny (≥ 1.7.4), golem (≥ 0.3.5), rlang (≥ 1.0.6), glmnet (≥ 4.1-6), loadeR (≥ 1.1.3), shinyjs (≥ 2.1.0), traineR (≥ 2.0.4), shinyAce (≥ 0.4.2), echarts4r (≥ 0.4.4), htmltools (≥ 0.5.4), rpart.plot (≥ 3.1.1), shinydashboard (≥ 0.7.2), shinycustomloader (≥ 0.9.0), shinydashboardPlus (≥ 2.0.3) |
| Published: | 2023-06-29 |
| Author: | Oldemar Rodriguez [aut, cre], Diego Jimenez A. [ctb, prg] |
| Maintainer: | Oldemar Rodriguez <oldemar.rodriguez at ucr.ac.cr> |
| BugReports: | https://github.com/PROMiDAT/predictoR/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://promidat.website/,https://github.com/PROMiDAT/regressoR |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | regressoR results |
| Reference manual: | regressoR.pdf |
| Package source: | regressoR_3.0.2.tar.gz |
| Windows binaries: | r-devel: regressoR_3.0.2.zip, r-release: regressoR_3.0.2.zip, r-oldrel: regressoR_3.0.2.zip |
| macOS binaries: | r-release (arm64): regressoR_3.0.2.tgz, r-oldrel (arm64): regressoR_3.0.2.tgz, r-release (x86_64): regressoR_3.0.2.tgz, r-oldrel (x86_64): regressoR_3.0.2.tgz |
| Old sources: | regressoR 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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