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fmeffects
View on CRAN: Click
here
Download and install fmeffects package within the R console
Install from CRAN:
install.packages("fmeffects")
Install from Github:
library("remotes")
install_github("cran/fmeffects")
Install by package version:
library("remotes")
install_version("fmeffects", "0.1.3")
Attach the package and use:
library("fmeffects")
Maintained by
Holger Löwe
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-07-19
Latest Update: 2023-09-26
Description:
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) .
How to cite:
Holger Löwe (2023). fmeffects: Model-Agnostic Interpretations with Forward Marginal Effects. R package version 0.1.3, https://cran.r-project.org/web/packages/fmeffects. Accessed 06 Nov. 2024.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for fmeffects
Functions, R codes and Examples using
the fmeffects R package
Some associated functions: AverageMarginalEffects . ForwardMarginalEffect . Partitioning . PartitioningCtree . PartitioningRpart . Predictor . PredictorCaret . PredictorMLR3 . PredictorParsnip . ame . bikes . came . fme . fmeffects-package . makePredictor . plot.ForwardMarginalEffect . plot.Partitioning . print.ForwardMarginalEffect . print.Partitioning . summary.AverageMarginalEffects . summary.ForwardMarginalEffect . summary.Partitioning .
Some associated R codes: ExtrapolationDetector.R . FME.R . FMEPlot.R . NonLinearityMeasure.R . Partitioning.R . PartitioningCtree.R . PartitioningPlot.R . PartitioningRpart.R . Predictor.R . PredictorCaret.R . PredictorMLR3.R . PredictorParsnip.R . Pruner.R . S3.R . ame.R . bikes.R . misc.R . zzz.R . Full fmeffects package functions and examples
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