shinyML: Compare H20 or Spark Supervised Regression Models Using Shiny App

Implementation of a shiny app to easily compare supervised regression model performances. You provide the data and configure each model parameter directly on the shiny app. Four main supervised learning algorithms can be tested either on Spark or H2O frameworks to suit your regression problem on a given time series. Implementation of these time series forecasting methods on R has been done by Shmueli and Lichtendahl (2015, ISBN:0991576632).

Version: 0.2.0
Depends: dplyr, data.table
Imports: shiny (≥ 1.0.3), shinydashboard, h2o, shinyWidgets, dygraphs, plotly, sparklyr, tidyr, DT, ggplot2, shinycssloaders
Suggests: knitr, rmarkdown, covr, testthat
Published: 2019-10-29
Author: Jean Bertin
Maintainer: Jean Bertin <jean.bertin at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: shinyML results


Reference manual: shinyML.pdf
Vignettes: Getting started with shinyML
Package source: shinyML_0.2.0.tar.gz
Windows binaries: r-devel:, r-devel-gcc8:, r-release:, r-oldrel:
OS X binaries: r-release: shinyML_0.2.0.tgz, r-oldrel: shinyML_0.2.0.tgz
Old sources: shinyML archive


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