Package: glmtree 0.3.1

Adrien Ehrhardt

glmtree: Logistic Regression Trees

A logistic regression tree is a decision tree with logistic regressions at its leaves. A particular stochastic expectation maximization algorithm is used to draw a few good trees, that are then assessed via the user's criterion of choice among BIC / AIC / test set Gini. The formal development is given in a PhD chapter, see Ehrhardt (2019) <https://github.com/adimajo/manuscrit_these/releases/>.

Authors:Adrien Ehrhardt [aut, cre]

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glmtree.pdf |glmtree.html
glmtree/json (API)

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

Peer review:

Bug tracker:https://github.com/adimajo/glmtree/issues

On CRAN:

4.78 score 6 stars 3 scripts 182 downloads 2 mentions 3 exports 80 dependencies

Last updated 9 months agofrom:aaec00a7e1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winOKOct 31 2024
R-4.5-linuxOKOct 31 2024
R-4.4-winOKOct 31 2024
R-4.4-macOKOct 31 2024
R-4.3-winOKOct 31 2024
R-4.3-macOKOct 31 2024

Exports:generateDataglmtreenormalizedGini

Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachFormulafuturefuture.applygenericsggplot2globalsgluegowergtablehardhatinumipredisobanditeratorsKernSmoothlabelinglatticelavalibcoinlifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellmvtnormnlmennetnumDerivparallellypartykitpillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr

glmtree: logistic regression trees for efficient segmentation

Rendered fromglmtree.Rmdusingknitr::rmarkdownon Oct 31 2024.

Last update: 2024-03-05
Started: 2019-07-16