The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Implementation of a shiny app to easily compare supervised machine learning model performances. You provide the data and configure each model parameter directly on the shiny app. Different supervised learning algorithms can be tested either on Spark or H2O frameworks to suit your regression and classification tasks. Implementation of available machine learning models on R has been done by Lantz (2013, ISBN:9781782162148).
Version: | 1.0.1 |
Depends: | dplyr, data.table |
Imports: | shiny (≥ 1.0.3), argonDash, argonR, shinyjs, h2o, shinyWidgets, dygraphs, plotly, sparklyr, tidyr, DT, ggplot2, shinycssloaders, lubridate, graphics |
Suggests: | knitr, rmarkdown, covr, testthat |
Published: | 2021-02-24 |
DOI: | 10.32614/CRAN.package.shinyML |
Author: | Jean Bertin |
Maintainer: | Jean Bertin <jean.bertin at mines-paris.org> |
BugReports: | https://github.com/JeanBertinR/shinyML/issues |
License: | GPL-3 |
URL: | https://jeanbertinr.github.io/shinyMLpackage/ |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | shinyML results |
Reference manual: | shinyML.pdf |
Package source: | shinyML_1.0.1.tar.gz |
Windows binaries: | r-devel: shinyML_1.0.1.zip, r-release: shinyML_1.0.1.zip, r-oldrel: shinyML_1.0.1.zip |
macOS binaries: | r-release (arm64): shinyML_1.0.1.tgz, r-oldrel (arm64): shinyML_1.0.1.tgz, r-release (x86_64): shinyML_1.0.1.tgz, r-oldrel (x86_64): shinyML_1.0.1.tgz |
Old sources: | shinyML archive |
Please use the canonical form https://CRAN.R-project.org/package=shinyML 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.