CoOL
1.1.2Causes of Outcome Learning
Overview
Implementing the computational phase of the Causes of Outcome Learning approach as described in Rieckmann, Dworzynski, Arras, Lapuschkin, Samek, Arah, Rod, Ekstrom. 2022. Causes of outcome learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome. International Journal of Epidemiology doi:10.1093/ije/dyac078. The optional 'ggtree' package can be obtained through Bioconductor.
Install
Health
CRAN check results are not tracked yet.
Documentation
- Examples that run
- 100%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- References docs
- 75%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
5 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2025-12-25issues were not addressed in time
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.1.22022-05-24 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 1.0.32021-07-16 · diff ↗
- 1.0.22021-06-30 · diff ↗
- RR 4.1.0 released · 2021-05-18
- 1.0.12021-02-23 · diff ↗
- 1.02021-02-12
- RR 4.0.0 released · 2020-04-24
Package metadata
- Total releases
- 5
- License
- GPL-2 OSI
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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