pomodoro: Predictive Power of Linear and Tree Modeling

Runs generalized and multinominal logistic (GLM and MLM) models, as well as random forest (RF), Bagging (BAG), and Boosting (BOOST). This package prints out to predictive outcomes easy for the selected data and data splits.

Version: 3.8.0
Depends: R (≥ 2.10)
Imports: tibble, caret, gbm, stats, randomForest, pROC, ipred
Suggests: knitr, rmarkdown
Published: 2022-03-26
Author: Seyma Kalay
Maintainer: Seyma Kalay <seymakalay at hotmail.com>
BugReports: https://github.com/seymakalay/pomodoro/issues
License: GPL-3
URL: https://github.com/seymakalay/pomodoro, https://seymakalay.github.io/pomodoro/
NeedsCompilation: no
Materials: README
CRAN checks: pomodoro results

Documentation:

Reference manual: pomodoro.pdf
Vignettes: Pomodoro_Vignette

Downloads:

Package source: pomodoro_3.8.0.tar.gz
Windows binaries: r-devel: pomodoro_3.8.0.zip, r-release: pomodoro_3.8.0.zip, r-oldrel: pomodoro_3.8.0.zip
macOS binaries: r-release (arm64): pomodoro_3.8.0.tgz, r-oldrel (arm64): pomodoro_3.8.0.tgz, r-release (x86_64): pomodoro_3.8.0.tgz, r-oldrel (x86_64): pomodoro_3.8.0.tgz
Old sources: pomodoro archive

Linking:

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