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: | 0.2 |
| Imports: | partykit, magrittr, methods, dplyr, caret |
| Suggests: | FactoMineR, knitr, testthat, covr, rmarkdown |
| Published: | 2020-10-03 |
| 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 |
| Reference manual: | glmtree.pdf |
| Vignettes: |
'glmtree' package |
| Package source: | glmtree_0.2.tar.gz |
| Windows binaries: | r-devel: glmtree_0.2.zip, r-release: glmtree_0.2.zip, r-oldrel: glmtree_0.2.zip |
| macOS binaries: | r-release (arm64): glmtree_0.2.tgz, r-oldrel (arm64): glmtree_0.2.tgz, r-release (x86_64): glmtree_0.2.tgz, r-oldrel (x86_64): glmtree_0.2.tgz |
| Old sources: | glmtree archive |
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