Building Predictive Models with Stacking
Overview
Building predictive models with stacking which is a type of ensemble learning. Learners can be specified from those implemented in 'caret'. For more information of the package, see Nukui and Onogi (2023) doi:10.1101/2023.06.06.543970.
Install
Health
- OK13 OK2026-08-04
- 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
- 5
- Examples that run
- 100%4 run in a plain check
- Exported functions with examples
- 80%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 0%
Downloads
Dependencies
Installing stacking adds 63 packages (34 with compiled code, 48 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
People & History
Package metadata
- First published
- 2023-06-11
- Total releases
- 5 / 3 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 10 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("stacking")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-17, which the citation names so these numbers can be found later. More on citing and the projects behind them.