corrgrapher: Explore Correlations Between Variables in a Machine Learning
Model
When exploring data or models we often examine variables one by one.
This analysis is incomplete if the relationship between these variables is
not taken into account. The 'corrgrapher' package facilitates simultaneous
exploration of the Partial Dependence Profiles and the correlation between
variables in the model.
The package 'corrgrapher' is a part of the 'DrWhy.AI' universe.
Version: |
1.0.4 |
Depends: |
R (≥ 3.5.0) |
Imports: |
visNetwork, ingredients, htmltools, ggplot2, knitr |
Suggests: |
rmarkdown, testthat, DALEX, gbm, ranger, spelling, covr |
Published: |
2020-10-13 |
Author: |
Pawel Morgen [aut, cre],
Przemyslaw Biecek [aut] |
Maintainer: |
Pawel Morgen <seriousmorgen at protonmail.com> |
BugReports: |
https://github.com/ModelOriented/corrgrapher/issues |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: |
https://modeloriented.github.io/corrgrapher/,
https://github.com/ModelOriented/corrgrapher |
NeedsCompilation: |
no |
Language: |
en-US |
Materials: |
README NEWS |
CRAN checks: |
corrgrapher results |
Documentation:
Downloads:
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