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: | 1.1.2 |
| 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), plyr (≥ 1.8.4) |
| Published: | 2020-06-26 |
| 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 |
| Reference manual: | predictoR.pdf |
| Package source: | predictoR_1.1.2.tar.gz |
| Windows binaries: | r-devel: predictoR_1.1.2.zip, r-release: predictoR_1.1.2.zip, r-oldrel: predictoR_1.1.2.zip |
| macOS binaries: | r-release: predictoR_1.1.2.tgz, r-oldrel: predictoR_1.1.2.tgz |
| Old sources: | predictoR archive |
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