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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 |
DOI: | 10.32614/CRAN.package.regressoR |
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 |
Please use the canonical form https://CRAN.R-project.org/package=regressoR to link to this page.
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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