Package: gbts 1.2.0
gbts: Hyperparameter Search for Gradient Boosted Trees
An implementation of hyperparameter optimization for Gradient Boosted Trees on binary classification and regression problems. The current version provides two optimization methods: Bayesian optimization and random search. Instead of giving the single best model, the final output is an ensemble of Gradient Boosted Trees constructed via the method of ensemble selection.
Authors:
gbts_1.2.0.tar.gz
gbts_1.2.0.zip(r-4.7)gbts_1.2.0.zip(r-4.6)gbts_1.2.0.zip(r-4.5)
gbts_1.2.0.tgz(r-4.6-any)gbts_1.2.0.tgz(r-4.5-any)
gbts_1.2.0.tar.gz(r-4.7-any)gbts_1.2.0.tar.gz(r-4.6-any)
gbts_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
gbts/json (API)
NEWS
| # Install 'gbts' in R: |
| install.packages('gbts', repos = c('https://wliang10.r-universe.dev', 'https://cloud.r-project.org')) |
- boston_housing - Boston housing data
- german_credit - German credit data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:8868614fb9. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 175 | ||
| source / vignettes | OK | 142 | ||
| linux-release-x86_64 | OK | 199 | ||
| macos-release-arm64 | OK | 124 | ||
| macos-oldrel-arm64 | OK | 174 | ||
| windows-devel | OK | 84 | ||
| windows-release | OK | 72 | ||
| windows-oldrel | OK | 88 | ||
| wasm-release | OK | 94 |
Dependencies:codetoolsdigestdoParalleldoRNGearthforeachFormulagbmiteratorslatticeMatrixplotmoplotrixrngtoolssurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Boston housing data | boston_housing |
| Compute model performance | comperf |
| Hyperparameter Search for Gradient Boosted Trees | gbts-package gbts |
| German credit data | german_credit |
| Predict method for ensemble of Gradient Boosted Trees | predict.gbts |
