modelStudio: Interactive Studio for Explanatory Model Analysis

Automate the explanatory analysis of machine learning predictive models. Generate advanced interactive model explanations in the form of a serverless HTML site with only one line of code. This tool is model agnostic, therefore compatible with most of the black box predictive models and frameworks. The main function computes various (instance and dataset level) model explanations and produces a customisable dashboard, which consists of multiple panels for plots with their short descriptions. Easily save the dashboard and share it with others. Tools for Explanatory Model Analysis unite with tools for Exploratory Data Analysis to give a broad overview of the model behavior.

Version: 2.0.0
Depends: R (≥ 3.5)
Imports: DALEX (≥ 2.0), ingredients (≥ 2.0), iBreakDown (≥ 1.3.1), r2d3, jsonlite, progress, digest
Suggests: parallelMap, ranger, xgboost, knitr, rmarkdown, testthat, spelling
Published: 2020-09-10
Author: Hubert Baniecki ORCID iD [aut, cre], Przemyslaw Biecek ORCID iD [aut], Piotr Piatyszek [ctb]
Maintainer: Hubert Baniecki <hbaniecki at gmail.com>
BugReports: https://github.com/ModelOriented/modelStudio/issues
License: GPL-3
URL: https://modelstudio.drwhy.ai, https://github.com/ModelOriented/modelStudio
NeedsCompilation: no
Language: en-US
Citation: modelStudio citation info
Materials: NEWS
CRAN checks: modelStudio results

Downloads:

Reference manual: modelStudio.pdf
Vignettes: modelStudio - perks and features
modelStudio - R & Python examples
Package source: modelStudio_2.0.0.tar.gz
Windows binaries: r-devel: modelStudio_2.0.0.zip, r-release: modelStudio_2.0.0.zip, r-oldrel: modelStudio_2.0.0.zip
macOS binaries: r-release: modelStudio_2.0.0.tgz, r-oldrel: modelStudio_2.0.0.tgz
Old sources: modelStudio archive

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