Package: FACT 0.1.1

FACT: Feature Attributions for ClusTering

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>.

Authors:Henri Funk [aut, cre], Christian Scholbeck [aut, ctb], Giuseppe Casalicchio [aut, ctb]

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FACT.pdf |FACT.html✨
FACT/json (API)
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Bug tracker:https://github.com/henrifnk/fact/issues

On CRAN:

3 exports 6 stars 1.26 score 42 dependencies 3 scripts 265 downloads

Last updated 6 months agofrom:80719b8721. Checks:OK: 4 NOTE: 2 ERROR: 1. Indexed: yes.

Exports:ClustPredictorIDEASMART

Dependencies:backportscheckmateclicodetoolscolorspacedata.tabledigestfansifarverFormulafuturefuture.applyggplot2globalsgluegridExtragtableimlisobandlabelinglatticelifecyclelistenvmagrittrMASSMatrixMetricsmgcvmunsellnlmeparallellypillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr