FFTrees: Generate, Visualise, and Evaluate Fast-and-Frugal Decision Trees

Create, visualize, and test fast-and-frugal decision trees (FFTs) using methods described in Phillips, Neth, Woike & Gaissmaier. (2017). FFTs are very simple decision trees for binary classification problems. FFTs can be preferable to more complex algorithms because they are easy to communicate, require very little information, and are robust against overfitting.

Version: 1.6.6
Depends: R (≥ 3.5.0)
Imports: rpart, graphics, randomForest, e1071, crayon, scales, tibble, stringr, progress, caret, dplyr, testthat, magrittr, tidyselect
Suggests: knitr, rmarkdown
Published: 2022-07-18
Author: Nathaniel Phillips [aut, cre], Hansjoerg Neth [aut], Jan Woike [aut], Wolfgang Gaissmaer [aut]
Maintainer: Nathaniel Phillips <Nathaniel.D.Phillips.is at gmail.com>
BugReports: https://github.com/ndphillips/FFTrees/issues
License: CC0
NeedsCompilation: no
Materials: README
CRAN checks: FFTrees results


Reference manual: FFTrees.pdf
Vignettes: Accuracy Statistics
Examples of FFTrees
Creating FFTrees with FFTrees()
Creating FFTs for heart disease
Manually specifying FFTs
Visualizing FFTrees with plot()
FFTrees package overview


Package source: FFTrees_1.6.6.tar.gz
Windows binaries: r-devel: FFTrees_1.6.6.zip, r-release: FFTrees_1.6.6.zip, r-oldrel: FFTrees_1.6.6.zip
macOS binaries: r-release (arm64): FFTrees_1.6.6.tgz, r-oldrel (arm64): FFTrees_1.6.6.tgz, r-release (x86_64): FFTrees_1.6.6.tgz, r-oldrel (x86_64): FFTrees_1.6.6.tgz
Old sources: FFTrees archive


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