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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=predictoR to link to this page.
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