predictoR: Predictive Data Analysis System

Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as K-Nearest Neighbors, Decision Trees, ADA Boosting, Extreme Gradient Boosting, Random Forest, Neural Networks, Deep Learning, Support Vector Machines and Bayesian Methods.

Version: 1.1.0
Depends: R (≥ 3.5)
Imports: shiny (≥ 1.2.0), shinyAce (≥ 0.3.3), shinydashboardPlus (≥ 0.6.0), shinyWidgets (≥ 0.4.4), shinyjs (≥ 1.0), flexdashboard (≥ 0.5.1.1), tidyverse (≥ 1.2.1), neuralnet (≥ 1.44.2), rpart (≥ 4.1-13), rattle (≥ 5.2.0), xgboost (≥ 0.81.0.1), ada (≥ 2.0-5), colourpicker (≥ 1.0), DT (≥ 0.5), randomForest (≥ 4.6-14), e1071 (≥ 1.7-0.1), kknn (≥ 1.3.1), glmnet (≥ 2.0-16), corrplot (≥ 0.84), ROCR (≥ 1.0-7), zip (≥ 1.0.0)
Published: 2019-06-24
Author: Oldemar Rodriguez R. with contributions from Diego Jimenez A. and Andres Navarro D.
Maintainer: Oldemar Rodriguez <oldemar.rodriguez at ucr.ac.cr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.promidat.com
NeedsCompilation: no
CRAN checks: predictoR results

Downloads:

Reference manual: predictoR.pdf
Package source: predictoR_1.1.0.tar.gz
Windows binaries: r-devel: predictoR_1.1.0.zip, r-devel-gcc8: predictoR_1.1.0.zip, r-release: predictoR_1.1.0.zip, r-oldrel: predictoR_1.1.0.zip
OS X binaries: r-release: predictoR_1.1.0.tgz, r-oldrel: predictoR_1.1.0.tgz
Old sources: predictoR archive

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