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: | 4.1.5 |
| Depends: | R (≥ 4.1) |
| Imports: | DT (≥ 0.27),dplyr (≥ 1.1.0),shiny (≥ 1.7.4),golem (≥0.3.5),rlang (≥ 1.0.6),loadeR (≥ 1.0.1),config (≥ 0.3.1),glmnet (≥ 4.1-6),traineR (≥ 2.2.0),shinyjs (≥ 2.1.0),xgboost (≥ 1.7.3.1),shinyAce (≥ 0.4.2),echarts4r (≥0.4.4),htmltools (≥ 0.5.4),rpart.plot (≥ 3.1.1),colourpicker (≥ 1.1.1),shinydashboard (≥ 0.7.2),shinycustomloader (≥ 0.9.0),shinydashboardPlus (≥ 2.0.3) |
| Published: | 2025-05-28 |
| DOI: | 10.32614/CRAN.package.predictoR |
| Author: | Oldemar Rodriguez [aut, cre], Diego Jiménez [ctb, prg], Andrés Navarro [ctb, prg] |
| Maintainer: | Oldemar Rodriguez <oldemar.rodriguez at ucr.ac.cr> |
| BugReports: | https://github.com/PROMiDAT/predictoR/issues |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://promidat.website/ |
| NeedsCompilation: | no |
| Language: | en-US |
| CRAN checks: | predictoR results[issues need fixing before 2025-12-22] |