When there is a tree: three segments, three regressions | When there is no tree: apparent clusters but a single regression | Choosing the best tree | Comparison with a clustering of the features
Package: glmtree 0.4.0
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:
glmtree_0.4.0.tar.gz
glmtree_0.4.0.zip(r-4.7-any)glmtree_0.4.0.zip(r-4.6-any)glmtree_0.4.0.zip(r-4.5-any)
glmtree_0.4.0.tgz(r-4.6-any)glmtree_0.4.0.tgz(r-4.5-any)
glmtree_0.4.0.tar.gz(r-4.7-any)glmtree_0.4.0.tar.gz(r-4.6-any)
glmtree_0.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
glmtree/json (API)
| # Install 'glmtree' in R: |
| install.packages('glmtree', repos = c('https://adimajo.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/adimajo/glmtree/issues
Pkgdown/docs site:https://adimajo.github.io
Last updated from:429bfd53db. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 148 | ||
| source / vignettes | OK | 209 | ||
| linux-release | OK | 149 | ||
| macos-release | OK | 98 | ||
| macos-oldrel | OK | 112 | ||
| windows-devel | OK | 238 | ||
| windows-release | OK | 136 | ||
| windows-oldrel | OK | 100 | ||
| wasm-release | OK | 115 |
Exports:generateDataglmtreenormalizedGinipredictprintshow
Dependencies:FormulainumlatticelibcoinMatrixmvtnormpartykitrpartsandwichstrucchangesurvivalzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Generates data from two logistic regression trees. | generateData |
| Logistic regression tree by Stochastic-Expectation-Maximization | glmtree |
| Class glmtree | glmtree-class print,glmtree-method show,glmtree-method |
| Calculating the normalized Gini index | normalizedGini |
| Prediction of a logistic regression tree | predict predict,glmtree-method |