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: | 0.1 |
| Imports: | partykit, magrittr, methods, dplyr, caret |
| Suggests: | FactoMineR, knitr, testthat, covr, rmarkdown |
| Published: | 2019-10-06 |
| 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 |
| CRAN checks: | glmtree results |
| Reference manual: | glmtree.pdf |
| Vignettes: |
'glmtree' package |
| Package source: | glmtree_0.1.tar.gz |
| Windows binaries: | r-devel: glmtree_0.1.zip, r-release: glmtree_0.1.zip, r-oldrel: glmtree_0.1.zip |
| macOS binaries: | r-release: glmtree_0.1.tgz, r-oldrel: glmtree_0.1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=glmtree to link to this page.