Package: fmeffects 0.1.4

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_0.1.4.tar.gz
fmeffects_0.1.4.zip(r-4.7)fmeffects_0.1.4.zip(r-4.6)fmeffects_0.1.4.zip(r-4.5)
fmeffects_0.1.4.tgz(r-4.6-any)fmeffects_0.1.4.tgz(r-4.5-any)
fmeffects_0.1.4.tar.gz(r-4.7-any)fmeffects_0.1.4.tar.gz(r-4.6-any)
fmeffects_0.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
fmeffects/json (API)
NEWS

# Install 'fmeffects' in R:

install.packages('fmeffects', repos = c('https://holgstr.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/holgstr/fmeffects/issues

Pkgdown/docs site:https://holgstr.github.io

Datasets:

bikes - Regression data of the usage of rental bikes in Washington D.C., USA

On CRAN:

4.01 score 2 stars 11 scripts 4.7k downloads 14 exports 48 dependencies

Last updated from:12331c401b. Checks:7 WARNING, 1 ERROR, 1 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	WARNING	212
source / vignettes	ERROR	278
linux-release-x86_64	WARNING	208
macos-release-arm64	WARNING	197
macos-oldrel-arm64	WARNING	439
windows-devel	WARNING	159
windows-release	WARNING	130
windows-oldrel	WARNING	140
wasm-release	OK	148

Exports:ame AverageMarginalEffects came fme ForwardMarginalEffect makePredictor Partitioning PartitioningCtree PartitioningRpart Predictor PredictorCaret PredictorLM PredictorMLR3 PredictorParsnip

Dependencies:backports brio callr checkmate cli cowplot cpp11 crayon data.table desc diffobj evaluate farver Formula fs ggparty ggplot2 glue gtable inum isoband jsonlite labeling lattice libcoin lifecycle magrittr Matrix mvtnorm partykit pkgbuild pkgload praise processx ps R6 RColorBrewer rlang rpart rprojroot S7 scales survival testthat vctrs viridisLite waldo withr

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Help page	Topics
fmeffects	fmeffects-package fmeffects
Computes AMEs for every feature (or a subset of features) of a model.	ame
R6 Class computing Average Marginal Effects (AME) based on Forward Marginal Effects (FME) for a model	AverageMarginalEffects
Regression data of the usage of rental bikes in Washington D.C., USA	bikes
Computes a partitioning for a 'ForwardMarginalEffect'	came
Computes FMEs.	fme
R6 Class representing a forward marginal effect (FME)	ForwardMarginalEffect
User-friendly function to create a Predictor.	makePredictor
R6 Class representing a partitioning	Partitioning
PartitioningCtree	PartitioningCtree
PartitioningRpart	PartitioningRpart
Plots an ForwardMarginalEffect object.	plot.ForwardMarginalEffect
Plots an FME Partitioning.	plot.Partitioning
R6 Class representing a predictor	Predictor
PredictorCaret	PredictorCaret
PredictorLM	PredictorLM
PredictorMLR3	PredictorMLR3
PredictorParsnip	PredictorParsnip
Prints an ForwardMarginalEffect object.	print.ForwardMarginalEffect
Prints an FME Partitioning.	print.Partitioning
Prints summary of an AverageMarginalEffects object.	summary.AverageMarginalEffects
Prints summary of an ForwardMarginalEffect object.	summary.ForwardMarginalEffect
Prints summary of an FME Partitioning.	summary.Partitioning

Package: fmeffects 0.1.4

fmeffects: Model-Agnostic Interpretations with Forward Marginal Effects

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