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: | 2.1.0 |
Depends: | R (≥ 3.5) |
Imports: | DALEX (≥ 2.0.1), ingredients (≥ 2.0), iBreakDown (≥ 1.3.1), r2d3, jsonlite, progress, digest |
Suggests: | parallelMap, ranger, xgboost, knitr, rmarkdown, testthat, spelling |
Published: | 2020-11-22 |
Author: | Hubert Baniecki |
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 |
Reference manual: | modelStudio.pdf |
Vignettes: |
modelStudio - perks and features modelStudio - R & Python examples |
Package source: | modelStudio_2.1.0.tar.gz |
Windows binaries: | r-devel: modelStudio_2.1.0.zip, r-release: modelStudio_2.1.0.zip, r-oldrel: modelStudio_2.1.0.zip |
macOS binaries: | r-release: modelStudio_2.1.0.tgz, r-oldrel: modelStudio_2.1.0.tgz |
Old sources: | modelStudio archive |
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