iml

Interpretable Machine Learning

Interpretability methods to analyze the behavior and predictions of any machine learning model. Implemented methods are: Feature importance described by Fisher et al. (2018) <arXiv:1801.01489>, partial dependence plots described by Friedman (2001) <http://www.jstor.org/stable/2699986>, individual conditional expectation ('ice') plots described by Goldstein et al. (2013) <doi:10.1080/10618600.2014.907095>, local models (variant of 'lime') described by Ribeiro et. al (2016) <arXiv:1602.04938>, the Shapley Value described by Strumbelj et. al (2014) <doi:10.1007/s10115-013-0679-x>, feature interactions described by Friedman et. al <doi:10.1214/07-AOAS148> and tree surrogate models.

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Description file content

Package
iml
Type
Package
Title
Interpretable Machine Learning
Version
0.5.1
Date
2018-04-27
Maintainer
Christoph Molnar
Description
Interpretability methods to analyze the behavior and predictions of any machine learning model. Implemented methods are: Feature importance described by Fisher et al. (2018) , partial dependence plots described by Friedman (2001) , individual conditional expectation ('ice') plots described by Goldstein et al. (2013) , local models (variant of 'lime') described by Ribeiro et. al (2016) , the Shapley Value described by Strumbelj et. al (2014) , feature interactions described by Friedman et. al and tree surrogate models.
URL
BugReports
https://github.com/christophM/iml/issues
Imports
R6, checkmate, ggplot2, partykit, glmnet, Metrics, data.table
Suggests
randomForest, gower, testthat, rpart, MASS, caret, e1071, lime, mlr, covr, knitr, rmarkdown
License
MIT + file LICENSE
RoxygenNote
6.0.1
VignetteBuilder
knitr
NeedsCompilation
no
Packaged
2018-05-15 07:04:14 UTC; chris
Author
Christoph Molnar [aut, cre]
Repository
CRAN
Date/Publication
2018-05-15 07:36:07 UTC

install.packages('iml')

0.5.1

2 months ago

https://github.com/christophM/iml

Christoph Molnar

MIT + file LICENSE

Imports

R6, checkmate, ggplot2, partykit, glmnet, Metrics, data.table

Suggests

randomForest, gower, testthat, rpart, MASS, caret, e1071, lime, mlr, covr, knitr, rmarkdown

Discussions