glmtree: Logistic Regression Trees (original) (raw)
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/>.
| Version: | 0.3.1 |
|---|---|
| Imports: | partykit, magrittr, methods, dplyr, caret |
| Suggests: | FactoMineR, knitr, testthat, covr, rmarkdown |
| Published: | 2024-03-06 |
| DOI: | 10.32614/CRAN.package.glmtree |
| Author: | Adrien Ehrhardt [aut, cre] |
| Maintainer: | Adrien Ehrhardt <adrien.ehrhardt at centraliens-lille.org> |
| BugReports: | https://github.com/adimajo/glmtree/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://adimajo.github.io |
| NeedsCompilation: | no |
| Citation: | glmtree citation info |
| CRAN checks: | glmtree results |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=glmtreeto link to this page.