Package: SplitSoftening 2.1-1
Jakub Dvorak
SplitSoftening: Softening Splits in Decision Trees
Allows to produce and use classification trees with soft (probability) splits, as described in: Dvořák, J. (2019), <doi:10.1007/s00180-019-00867-1>.
Authors:
SplitSoftening_2.1-1.tar.gz
SplitSoftening_2.1-1.tar.gz(r-4.5-noble)SplitSoftening_2.1-1.tar.gz(r-4.4-noble)
SplitSoftening_2.1-1.tgz(r-4.4-emscripten)SplitSoftening_2.1-1.tgz(r-4.3-emscripten)
SplitSoftening.pdf |SplitSoftening.html✨
SplitSoftening/json (API)
| # Install 'SplitSoftening' in R: |
| install.packages('SplitSoftening', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 days agofrom:0cdf62279b. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 28 2024 |
| R-4.5-linux-x86_64 | OK | Oct 28 2024 |
Exports:predictSoftsplitssoftensoftening.by.data.rangesoftening.by.esdsoftening.optimizedsoftsplits
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Prediction according to `soft tree'. | predictSoftsplits |
| Create a `soft tree' structure with softening parameters set using one of the named method. | soften |
| Make split softening based on data ranges. | softening.by.data.range |
| Soften splits separately using error standard deviation. | softening.by.esd |
| Make split softening optimized with Nelder-Mead. | softening.optimized |
| Create `soft tree' structure from a tree object. | softsplits |
| Package: Softening splits in classification trees | SplitSoftening |
