Package: imptree 0.5.1
imptree: Classification Trees with Imprecise Probabilities
Creation of imprecise classification trees. They rely on probability estimation within each node by means of either the imprecise Dirichlet model or the nonparametric predictive inference approach. The splitting variable is selected by the strategy presented in Fink and Crossman (2013) <http://www.sipta.org/isipta13/index.php?id=paper&paper=014.html>, but also the original imprecise information gain of Abellan and Moral (2003) <doi:10.1002/int.10143> is covered.
Authors:
imptree_0.5.1.tar.gz
imptree_0.5.1.zip(r-4.5)imptree_0.5.1.zip(r-4.4)imptree_0.5.1.zip(r-4.3)
imptree_0.5.1.tgz(r-4.5-x86_64)imptree_0.5.1.tgz(r-4.5-arm64)imptree_0.5.1.tgz(r-4.4-x86_64)imptree_0.5.1.tgz(r-4.4-arm64)imptree_0.5.1.tgz(r-4.3-x86_64)imptree_0.5.1.tgz(r-4.3-arm64)
imptree_0.5.1.tar.gz(r-4.5-noble)imptree_0.5.1.tar.gz(r-4.4-noble)
imptree_0.5.1.tgz(r-4.4-emscripten)imptree_0.5.1.tgz(r-4.3-emscripten)
imptree.pdf |imptree.html✨
imptree/json (API)
| # Install 'imptree' in R: |
| install.packages('imptree', repos = c('https://paul-fink.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/paul-fink/imptree/issues
- carEvaluation - Car Evaluation Database
Last updated 6 years agofrom:a1867d73bd. Checks:1 OK, 11 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 05 2025 |
| R-4.5-win-x86_64 | NOTE | Mar 05 2025 |
| R-4.5-mac-x86_64 | NOTE | Mar 05 2025 |
| R-4.5-mac-aarch64 | NOTE | Mar 05 2025 |
| R-4.5-linux-x86_64 | NOTE | Mar 05 2025 |
| R-4.4-win-x86_64 | NOTE | Mar 05 2025 |
| R-4.4-mac-x86_64 | NOTE | Mar 05 2025 |
| R-4.4-mac-aarch64 | NOTE | Mar 05 2025 |
| R-4.4-linux-x86_64 | NOTE | Mar 05 2025 |
| R-4.3-win-x86_64 | NOTE | Mar 05 2025 |
| R-4.3-mac-x86_64 | NOTE | Mar 05 2025 |
| R-4.3-mac-aarch64 | NOTE | Mar 05 2025 |
Exports:imptreeimptree_controlnode_imptreeprobInterval
Dependencies:Rcpp
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| imptree: Classification Trees with Imprecise Probabilities | imptree-package |
| Car Evaluation Database | carEvaluation |
| Classification Trees with Imprecise Probabilities | imptree imptree.default imptree.formula |
| Control parameters for generating imptree objects | imptree_control |
| Classification with Imprecise Probabilities | node_imptree print.node_imptree |
| Classification with Imprecise Probabilities | predict.imptree print.evaluation_imptree |
| Classification with Imprecise Probabilities | print.imptree |
| Various method around IPIntervals | probInterval |
| Classification with Imprecise Probabilities | print.summary.imptree summary.imptree |
