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: | 1.0.0 | 
| Depends: | R (≥ 3.2.0) | 
| 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 | 
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) | 
| Published: | 2025-10-13 | 
| 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 | 
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