Automatically builds 12 classification models from data. The package returns 26 plots, 5 tables and a summary report. The package automatically builds six individual classification models, including error (RMSE) and predictions. That data is used to create an ensemble, which is then modeled using six methods. The process is repeated as many times as the user requests. The mean of the results are presented in a summary table. The package returns the confusion matrices for all 12 models, tables of the correlation of the numeric data, the results of the variance inflation process, the head of the ensemble and the head of the data frame.
| Version: | 0.7.0 |
| Depends: | C50, car, caret, corrplot, doParallel, dplyr, e1071, ggplot2, gt, ipred, MachineShop, magrittr, parallel, pls, purrr, R (≥ 2.10), randomForest, ranger, reactable, reactablefmtr, scales, tidyr, tree |
| Suggests: | knitr, rmarkdown |
| Published: | 2025-10-12 |
| DOI: | 10.32614/CRAN.package.ClassificationEnsembles |
| Author: | Russ Conte [aut, cre, cph] |
| Maintainer: | Russ Conte <russconte at mac.com> |
| BugReports: | https://github.com/InfiniteCuriosity/ClassificationEnsembles/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/InfiniteCuriosity/ClassificationEnsembles |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | ClassificationEnsembles results |
| Reference manual: | ClassificationEnsembles.html , ClassificationEnsembles.pdf |
| Vignettes: |
ClassificationEnsembles-vignette (source) Template (source) |
| Package source: | ClassificationEnsembles_0.7.0.tar.gz |
| Windows binaries: | r-devel: ClassificationEnsembles_0.6.0.zip, r-release: ClassificationEnsembles_0.6.0.zip, r-oldrel: ClassificationEnsembles_0.7.0.zip |
| macOS binaries: | r-release (arm64): ClassificationEnsembles_0.7.0.tgz, r-oldrel (arm64): ClassificationEnsembles_0.7.0.tgz, r-release (x86_64): ClassificationEnsembles_0.7.0.tgz, r-oldrel (x86_64): ClassificationEnsembles_0.7.0.tgz |
| Old sources: | ClassificationEnsembles archive |
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