Package: shinyML 1.0.1

Jean Bertin

shinyML: 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).

Authors:Jean Bertin

shinyML_1.0.1.tar.gz
shinyML_1.0.1.zip(r-4.7-any)shinyML_1.0.1.zip(r-4.6-any)shinyML_1.0.1.zip(r-4.5-any)
shinyML_1.0.1.tgz(r-4.6-any)shinyML_1.0.1.tgz(r-4.5-any)
shinyML_1.0.1.tar.gz(r-4.7-any)shinyML_1.0.1.tar.gz(r-4.6-any)
shinyML_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
shinyML/json (API)

# Install 'shinyML' in R:

install.packages('shinyML', repos = c('https://jeanbertinr.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jeanbertinr/shinyml/issues

On CRAN:

4.60 score 61 stars 13 scripts 278 downloads 2 exports 94 dependencies

Last updated from:2aecbf230b. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	211
source / vignettes	OK	225
linux-release	OK	210
macos-release	OK	157
macos-oldrel	OK	205
windows-devel	OK	116
windows-release	OK	110
windows-oldrel	OK	110
wasm-release	OK	194

Exports:shinyML_classification shinyML_regression

Dependencies:argonDash argonR askpass base64enc bitops blob bslib cachem cli codetools commonmark config cpp11 crosstalk curl data.table DBI dbplyr digest dplyr DT dygraphs evaluate farver fastmap fontawesome fs generics ggplot2 globals glue gtable h2o highr htmltools htmlwidgets httpuv httr isoband jquerylib jsonlite knitr labeling later lattice lazyeval lifecycle lubridate magrittr memoise mime openssl otel pillar pkgconfig plotly promises purrr R6 rappdirs RColorBrewer Rcpp RCurl rlang rmarkdown rstudioapi S7 sass scales shiny shinycssloaders shinyjs shinyWidgets sourcetools sparklyr stringi stringr sys tibble tidyr tidyselect timechange tinytex utf8 uuid vctrs viridisLite withr xfun xml2 xtable xts yaml zoo

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Implement a shiny web app to compare h2o and Spark supervised machine learning models for classification tasks	shinyML_classification
Implement a shiny web app to compare h2o and Spark supervised machine learning models for regression tasks	shinyML_regression