Machine Learning Algorithms Fitting and Validation for Forestry
Overview
Fitting and validation of machine learning algorithms for volume prediction of trees, currently for conifer trees based on diameter at breast height and height as explanatory variables.
- The ImML() function was added.
- The EastCirclePine data set was added.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK13 OK2026-05-02
Show 2 earlier changesHide 2 earlier changes
- ERROR11 OK, 1 ERROR2026-04-25
- OK14 OK2026-03-10
Documentation
- Help pages
- 2
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 50%
Downloads
Dependencies
Installing ImML adds 64 packages (35 with compiled code, 48 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 0.1.5Latest2023-09-06 · current release
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2023-09-06
- Total releases
- 1 / 3 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 2.9 KB / 1 file
- Download size
- 7.6 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("ImML")The package provides a citation file, so citation() returns the authors' own entry.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.