CRAN/E | shinyML

shinyML

Compare Supervised Machine Learning Models Using Shiny App

Installation

About

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).

jeanbertinr.github.io/shinyMLpackage/
Bug report File report

Key Metrics

Version 1.0.1
Published 2021-02-24 1163 days ago
Needs compilation? no
License GPL-3
CRAN checks shinyML results

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Maintainer

Maintainer

Jean Bertin

jean.bertin@mines-paris.org

Authors

Jean Bertin

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

shinyML archive

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