gbm.auto: Automated Boosted Regression Tree Modelling and Mapping Suite
Automates delta log-normal boosted regression tree abundance prediction. Loops through parameters provided (LR (learning rate), TC (tree complexity), BF (bag fraction)), chooses best, simplifies, & generates line, dot & bar plots, & outputs these & predictions & a report, makes predicted abundance maps, and Unrepresentativeness surfaces. Package core built around 'gbm' (gradient boosting machine) functions in 'dismo' (Hijmans, Phillips, Leathwick & Jane Elith, 2020 & ongoing), itself built around 'gbm' (Greenwell, Boehmke, Cunningham & Metcalfe, 2020 & ongoing, originally by Ridgeway). Indebted to Elith/Leathwick/Hastie 2008 'Working Guide' <doi:10.1111/j.1365-2656.2008.01390.x>; workflow follows Appendix S3. See <https://www.simondedman.com/> for published guides and papers using this package.
| Version: | 2024.10.01 |
| Depends: | R (≥ 3.5.0) |
| Imports: | beepr (≥ 1.2),dismo (≥ 1.3-14),dplyr (≥ 1.0.9),gbm (≥2.1.1),ggmap (≥ 3.0.2),ggplot2 (≥ 3.4.2),ggspatial (≥1.1.9),lifecycle,lubridate (≥ 1.9.2),mapplots (≥ 1.5),Metrics (≥ 0.1.4),readr (≥ 2.1.4),sf (≥ 0.9-7),stars (≥0.6-3),starsExtra (≥ 0.2.7), stats (≥ 3.3.1),stringi (≥1.6.1),tidyselect (≥ 1.2.0),viridis (≥ 0.6.4) |
| Published: | 2024-10-01 |
| DOI: | 10.32614/CRAN.package.gbm.auto |
| Author: | Simon Dedman [aut, cre] |
| Maintainer: | Simon Dedman <simondedman at gmail.com> |
| License: | MIT + fileLICENSE |
| NeedsCompilation: | no |
| Language: | en-GB |
| Citation: | gbm.auto citation info |
| Materials: | README,NEWS |
| CRAN checks: | gbm.auto results |
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