We present 'FACT' (Feature Attributions for ClusTering), a framework for unsupervised interpretation methods that can be used with an arbitrary clustering algorithm. The package is capable of re-assigning instances to clusters (algorithm agnostic), preserves the integrity of the data and does not introduce additional models. 'FACT' is inspired by the principles of model-agnostic interpretation in supervised learning. Therefore, some of the methods presented are based on 'iml', a R Package for Interpretable Machine Learning by Christoph Molnar, Giuseppe Casalicchio, and Bernd Bischl (2018) <doi:10.21105/joss.00786>.
Version: 0.1.1 Imports: checkmate, data.table, ggplot2, gridExtra, R6, iml Suggests: testthat (≥ 3.0.0), caret, covr, knitr, mlr3, mlr3cluster, rmarkdown, FuzzyDBScan, factoextra, patchwork, spelling Published: 2024-03-25 DOI: 10.32614/CRAN.package.FACT Author: Henri Funk [aut, cre], Christian Scholbeck [aut, ctb], Giuseppe Casalicchio [aut, ctb] Maintainer: Henri Funk <Henri.Funk at stat.uni-muenchen.de> BugReports: https://github.com/henrifnk/FACT/issues License: LGPL-3 NeedsCompilation: no Language: en-US Materials: README NEWS CRAN checks: FACT results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=FACT to link to this page.
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