Package: fmeffects 0.1.3

fmeffects: Model-Agnostic Interpretations with Forward Marginal Effects

Create local, regional, and global explanations for any machine learning model with forward marginal effects. You provide a model and data, and 'fmeffects' computes feature effects. The package is based on the theory in: C. A. Scholbeck, G. Casalicchio, C. Molnar, B. Bischl, and C. Heumann (2022) <doi:10.48550/arXiv.2201.08837>.

Authors:Holger Löwe [cre, aut], Christian Scholbeck [aut], Christian Heumann [rev], Bernd Bischl [rev], Giuseppe Casalicchio [rev]

fmeffects_0.1.3.tar.gz
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fmeffects_0.1.3.tgz(r-4.4-any)fmeffects_0.1.3.tgz(r-4.3-any)
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fmeffects.pdf |fmeffects.html✨
fmeffects/json (API)
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Bug tracker:https://github.com/holgstr/fmeffects/issues

On CRAN:

14 exports 2 stars 1.68 score 58 dependencies 6 scripts 840 downloads

Last updated 3 months agofrom:020e2054af. Checks:OK: 6 ERROR: 1. Indexed: yes.

Exports:ameAverageMarginalEffectscamefmeForwardMarginalEffectmakePredictorPartitioningPartitioningCtreePartitioningRpartPredictorPredictorCaretPredictorLMPredictorMLR3PredictorParsnip

Dependencies:backportsbriocallrcheckmateclicolorspacecowplotcrayondata.tabledescdiffobjdigestevaluatefansifarverFormulafsggpartyggplot2gluegtableinumisobandjsonlitelabelinglatticelibcoinlifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmepartykitpillarpkgbuildpkgconfigpkgloadpraiseprocessxpsR6RColorBrewerrematch2rlangrpartrprojrootscalessurvivaltestthattibbleutf8vctrsviridisLitewaldowithr