Shed light on black box machine learning models by the help of model performance, permutation variable importance (Fisher et al. (2018) <arxiv:1801.01489>), ICE profiles, partial dependence (Friedman J. H. (2001) <doi:10.1214/aos/1013203451>), accumulated local effects (Apley D. W. (2016) <arXiv:1612.08468>), further effects plots, and variable contribution breakdown for single observations (Gosiewska and Biecek (2019) <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: | 0.3.0 |
Depends: | R (≥ 3.5.0) |
Imports: | stats, utils, dplyr, tidyr, rlang, ggplot2, ggpubr, MetricsWeighted (≥ 0.2.0) |
Suggests: | knitr, lubridate, ranger, xgboost, caret, moderndive |
Published: | 2019-10-13 |
Author: | Michael Mayer [aut, cre, cph] |
Maintainer: | Michael Mayer <mayermichael79 at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | flashlight results |
Reference manual: | flashlight.pdf |
Vignettes: |
flashlight |
Package source: | flashlight_0.3.0.tar.gz |
Windows binaries: | r-devel: flashlight_0.3.0.zip, r-release: flashlight_0.3.0.zip, r-oldrel: flashlight_0.3.0.zip |
OS X binaries: | r-release: flashlight_0.3.0.tgz, r-oldrel: flashlight_0.3.0.tgz |
Old sources: | flashlight archive |
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