Methods to unify the different ways of creating predictive models and their different predictive formats. It includes methods such as K-Nearest Neighbors, Decision Trees, ADA Boosting, Extreme Gradient Boosting, Random Forest, Neural Networks, Deep Learning, Support Vector Machines, Bayesian Methods, Linear Discriminant Analysis and Quadratic Discriminant Analysis, Logistic Regression, Penalized Logistic Regression.
| Version: | 1.6.2 |
| Depends: | R (≥ 3.5) |
| Imports: | neuralnet (≥ 1.44.2), rpart (≥ 4.1-13), xgboost (≥ 0.81.0.1), randomForest (≥ 4.6-14), e1071 (≥ 1.7-0.1), kknn (≥ 1.3.1), dplyr (≥ 0.8.0.1), MASS (≥ 7.3-53), ada (≥ 2.0-5), nnet (≥ 7.3-12), dummies (≥ 1.5.6), stringr (≥ 1.4.0), adabag, glmnet, ROCR, ggplot2, scales, glue, grDevices |
| Suggests: | knitr, rmarkdown, rpart.plot |
| Published: | 2021-06-03 |
| Author: | Oldemar Rodriguez R. [aut, cre], Andres Navarro D. [ctb, prg], Ariel Arroyo S. [ctb, prg] |
| Maintainer: | Oldemar Rodriguez R. <oldemar.rodriguez at ucr.ac.cr> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://www.promidat.com |
| NeedsCompilation: | no |
| CRAN checks: | traineR results |
| Reference manual: | traineR.pdf |
| Vignettes: |
traineR |
| Package source: | traineR_1.6.2.tar.gz |
| Windows binaries: | r-devel: traineR_1.6.2.zip, r-release: traineR_1.6.2.zip, r-oldrel: traineR_1.6.2.zip |
| macOS binaries: | r-release (arm64): traineR_1.6.2.tgz, r-release (x86_64): traineR_1.6.2.tgz, r-oldrel: traineR_1.6.2.tgz |
| Old sources: | traineR archive |
Please use the canonical form https://CRAN.R-project.org/package=traineR to link to this page.