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Automatically builds 20 classification models from data. The package returns 26 plots, 5 tables and a summary report. The package automatically builds 12 individual classification models, including error (RMSE) and predictions. That data is used to create an ensemble, which is then modeled using 8 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 20 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: | 0.5.0 |
| 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: | 2025-04-01 |
| 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.pdf |
| Vignettes: |
ClassificationEnsembles-vignette (source) |
| Package source: | ClassificationEnsembles_0.5.0.tar.gz |
| Windows binaries: | r-devel: ClassificationEnsembles_0.5.0.zip, r-release: ClassificationEnsembles_0.5.0.zip, r-oldrel: ClassificationEnsembles_0.5.0.zip |
| macOS binaries: | r-release (arm64): ClassificationEnsembles_0.5.0.tgz, r-oldrel (arm64): ClassificationEnsembles_0.5.0.tgz, r-release (x86_64): ClassificationEnsembles_0.5.0.tgz, r-oldrel (x86_64): ClassificationEnsembles_0.5.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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