Compare Supervised Machine Learning Models Using Shiny App

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).


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install.packages("shinyML")

1.0.0 by Jean Bertin, a month ago


Browse source code at https://github.com/cran/shinyML


Authors: Jean Bertin


Documentation:   PDF Manual  


GPL-3 license


Imports shiny, argonDash, argonR, shinyjs, shinydashboard, h2o, shinyWidgets, dygraphs, plotly, sparklyr, tidyr, DT, ggplot2, shinycssloaders, lubridate, lifecycle, graphics

Depends on dplyr, data.table

Suggests knitr, rmarkdown, covr, testthat


See at CRAN