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.
| Version: |
0.9.0 |
| Depends: |
R (≥ 3.2.0) |
| Imports: |
cowplot, dplyr (≥ 1.1.0), ggplot2, MetricsWeighted (≥
0.3.0), rlang (≥ 0.3.0), rpart, rpart.plot, stats, tibble, tidyr (≥ 1.0.0), tidyselect, utils, withr |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2023-05-10 |
| DOI: |
10.32614/CRAN.package.flashlight |
| Author: |
Michael Mayer [aut, cre, cph] |
| Maintainer: |
Michael Mayer <mayermichael79 at gmail.com> |
| BugReports: |
https://github.com/mayer79/flashlight/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://github.com/mayer79/flashlight |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
flashlight results |
Documentation:
Downloads:
Reverse dependencies:
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