Interpretability methods to analyze the behavior and predictions of any machine learning model. Implemented methods are: Feature importance described by Fisher et al. (2018) <doi:10.48550/arxiv.1801.01489>, accumulated local effects plots described by Apley (2018) <doi:10.48550/arxiv.1612.08468>, partial dependence plots described by Friedman (2001) <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) <doi:10.48550/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.
Version: 0.11.4 Imports: checkmate, data.table, Formula, future, future.apply, ggplot2, Metrics, R6 Suggests: ALEPlot, bench, bit64, caret, covr, e1071, future.callr, glmnet, gower, h2o, keras (≥ 2.2.5.0), knitr, MASS, mlr, mlr3, party, partykit, patchwork, randomForest, ranger, rmarkdown, rpart, testthat, yaImpute Published: 2025-02-24 DOI: 10.32614/CRAN.package.iml Author: Giuseppe Casalicchio [aut, cre], Christoph Molnar [aut], Patrick Schratz [aut] Maintainer: Giuseppe Casalicchio <giuseppe.casalicchio at lmu.de> BugReports: https://github.com/giuseppec/iml/issues License: MIT + file LICENSE URL: https://giuseppec.github.io/iml/, https://github.com/giuseppec/iml/ NeedsCompilation: no Citation: iml citation info Materials: NEWS In views: MachineLearning CRAN checks: iml resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4