flashlight
Shed Light on Black Box Machine Learning Models
Shed light on black box machine learning models by the help of model performance, variable importance, global surrogate models, ICE profiles, partial dependence (Friedman J. H. (2001) <doi:10.1214/aos/1013203451>), accumulated local effects (Apley D. W. (2016) <doi:10.48550/arXiv.1612.08468>), further effects plots, interaction strength, and variable contribution breakdown (Gosiewska and Biecek (2019) <doi:10.48550/arXiv.1903.11420>). All tools are implemented to work with case weights and allow for stratified analysis. Furthermore, multiple flashlights can be combined and analyzed together.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling source/ R- | flashlight_1.0.0.tar.gz |
430.3 KiB |
1.0.0 |
latest source/ R- | flashlight_1.0.0.tar.gz |
430.3 KiB |
1.0.0 |
2026-04-23 source/ R- | flashlight_1.0.0.tar.gz |
430.3 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | flashlight_1.0.0.zip |
624.4 KiB |
Dependencies (latest)
Imports
- dplyr (>= 1.1.0)
- ggplot2
- MetricsWeighted (>= 0.3.0)
- rlang (>= 0.3.0)
- rpart
- rpart.plot
- stats
- tibble
- tidyr (>= 1.0.0)
- tidyselect
- utils