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localModel: Local Explanations of Machine Learning Models for Tabular Data.

localModel is a successor to the live package. It implements a variant of LIME method for explaining single predictions of black box machine learning models for tabular data. Interpretable features are created based on Ceteris Paribus plots. Details of the methodology are described in the vignette. localModel is currently undergoing rapid changes, including bug fixes, for a stable solution please see the live package.

To get started, install the package from CRAN:

install.packages('localModel')

The development version can be installe from GitHub by using the code below. Please do not use the devtools package, since it is affected a bug which makes localModel installation impossible. This issue was solved in the Github version of remotes.

devtools::install_github("r-lib/remotes")
remotes::install_github("ModelOriented/localModel")

To get help, see examples and details of the methodology, please refer to package website and vignettes.

Acknowledgments

Work on this package is financially supported by the NCN Opus grant 2017/27/B/ST6/01307.

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Install

install.packages('localModel')

Monthly Downloads

855

Version

0.5

License

GPL

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Maintainer

Przemyslaw Biecek

Last Published

September 14th, 2021

Functions in localModel (0.5)

plot.local_surrogate_explainer

Generic plot function for local surrogate explainers
individual_surrogate_model

LIME-like explanations based on Ceteris Paribus curves
localModel

localModel: LIME-like explanations with interpretable features based on Ceteris Paribus profiles
print.local_surrogate_explainer

Generic print function for local surrogate explainers
gaussian_kernel

LIME kernel from the original article with sigma = 1.
identity_kernel

LIME kernel that treats all observations as equally similar to the observation of interest.
plot_interpretable_feature

Plot Ceteris Paribus Profile and discretization