Package: FFTrees 2.0.0.9000

Hansjoerg Neth

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

Create, visualize, and test fast-and-frugal decision trees (FFTs) using the algorithms and methods described by Phillips, Neth, Woike & Gaissmaier (2017), <doi:10.1017/S1930297500006239>. FFTs are simple and transparent decision trees for solving binary classification problems. FFTs can be preferable to more complex algorithms because they require very little information, are easy to understand and communicate, and are robust against overfitting.

Authors:Nathaniel Phillips [aut], Hansjoerg Neth [aut, cre], Jan Woike [aut], Wolfgang Gaissmaier [aut]

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FFTrees.pdf |FFTrees.html
FFTrees/json (API)
NEWS

# Install 'FFTrees' in R:
install.packages('FFTrees', repos = c('https://ndphillips.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ndphillips/fftrees/issues

Datasets:

On CRAN:

25 exports 135 stars 4.80 score 96 dependencies 148 scripts 431 downloads

Last updated 14 days agofrom:a04a7089ab. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 04 2024
R-4.5-winOKSep 04 2024
R-4.5-linuxOKSep 04 2024
R-4.4-winOKSep 04 2024
R-4.4-macOKSep 04 2024
R-4.3-winOKSep 04 2024
R-4.3-macOKSep 04 2024

Exports:add_fft_dfadd_nodesdescribe_datadrop_nodesedit_nodesFFTreesfftrees_applyfftrees_createfftrees_cuerankfftrees_definefftrees_ffttowordsfftrees_threshold_factor_gridfftrees_threshold_numeric_gridfftrees_wordstofftreesFFTrees.guideflip_exitsget_best_treeget_exit_typeget_fft_dfinwordsread_fft_dfreorder_nodesselect_nodesshowcueswrite_fft_df

Dependencies:briocallrcaretclasscliclockcodetoolscolorspacecpp11crayondata.tabledescdiagramdiffobjdigestdplyre1071evaluatefansifarverforeachfsfuturefuture.applygenericsggplot2globalsgluegowergtablehardhathighripredisobanditeratorsjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgbuildpkgconfigpkgloadplyrpraisepROCprocessxprodlimprogressrproxypspurrrR6RColorBrewerRcpprecipesrematch2reshape2rlangrpartrprojrootscalesshapeSQUAREMstringistringrsurvivaltestthattibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewaldowithrxfunyaml

Accuracy statistics in FFTrees

Rendered fromFFTrees_accuracy_statistics.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2024-05-21
Started: 2022-07-27

Creating FFTs with FFTrees()

Rendered fromFFTrees_function.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2024-05-21
Started: 2016-08-23

Examples of FFTrees

Rendered fromFFTrees_examples.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2024-07-20
Started: 2016-08-23

Manually specifying FFTs

Rendered fromFFTrees_mytree.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2024-07-20
Started: 2017-05-30

Overview: Creating FFTs with FFTrees

Rendered fromguide.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2024-05-21
Started: 2016-10-07

Tutorial: Creating FFTs for heart disease

Rendered fromFFTrees_heart.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2024-05-21
Started: 2017-06-21

Visualising FFTs

Rendered fromFFTrees_plot.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2024-05-21
Started: 2016-08-23

Readme and manuals

Help Manual

Help pageTopics
Add an FFT definition to tree definitionsadd_fft_df
Add nodes to an FFT definitionadd_nodes
Add decision statistics to data (based on frequency counts of a 2x2 matrix of classification outcomes)add_stats
Blood donation datablood
Breast cancer databreastcancer
Car acceptability datacar
Compute classification statistics for binary prediction and criterion (e.g.; truth) vectorsclasstable
Contraceptive use datacontraceptive
Credit approval datacreditapproval
Describe datadescribe_data
Drop a node from an FFT definitiondrop_nodes
Edit nodes in an FFT definitionedit_nodes
Clean factor variables in prediction datafact_clean
Fertility datafertility
Main function to create and apply fast-and-frugal trees (FFTs)FFTrees FFTrees-function
Calculate thresholds that optimize some statistic (goal) for cues in datafftrees_cuerank
Describe a fast-and-frugal tree (FFT) in wordsfftrees_ffttowords
Grow fast-and-frugal trees (FFTs) using the 'fan' algorithmsfftrees_grow_fan
Rank FFTs by current goalfftrees_ranktrees
Perform a grid search over factor and return accuracy statistics for a given factor cuefftrees_threshold_factor_grid
Perform a grid search over thresholds and return accuracy statistics for a given numeric cuefftrees_threshold_numeric_grid
Convert a verbal description of an FFT into an 'FFTrees' objectfftrees_wordstofftrees
Open the *FFTrees* package guideFFTrees.guide
Flip exits in an FFT definitionflip_exits
Forest fires dataforestfires
Select the best tree (from current set of FFTs)get_best_tree
Get exit type (from a vector 'x' of FFT exit descriptions)get_exit_type
Get FFT definitions (from an 'FFTrees' object 'x')get_fft_df
Cue costs for the 'heartdisease' dataheart.cost
Heart disease testing dataheart.test
Heart disease training dataheart.train
Heart disease dataheartdisease
Provide a verbal description of an FFTinwords
Iris datairis.v
Mushrooms datamushrooms
Plot an 'FFTrees' objectplot.FFTrees
Predict classification outcomes or probabilities from datapredict.FFTrees
Print basic information of fast-and-frugal trees (FFTs)print.FFTrees
Read an FFT definition from tree definitionsread_fft_df
Reorder nodes in an FFT definitionreorder_nodes
Select nodes from an FFT definitionselect_nodes
Visualize cue accuracies (as points in ROC space)showcues
Sonar datasonar
Summarize an 'FFTrees' objectsummary.FFTrees
Titanic survival datatitanic
Voting datavoting
Wine tasting datawine
Write an FFT definition to tree definitionswrite_fft_df