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) <arXiv:1612.08468>), further effects plots, interaction strength, and variable contribution breakdown (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.
Package details |
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Author | Michael Mayer [aut, cre, cph] |
Maintainer | Michael Mayer <mayermichael79@gmail.com> |
License | GPL (>= 2) |
Version | 0.9.0 |
URL | https://github.com/mayer79/flashlight |
Package repository | View on CRAN |
Installation |
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