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iBreakDown (version 1.3.1)

Model Agnostic Instance Level Variable Attributions

Description

Model agnostic tool for decomposition of predictions from black boxes. Supports additive attributions and attributions with interactions. The Break Down Table shows contributions of every variable to a final prediction. The Break Down Plot presents variable contributions in a concise graphical way. This package works for classification and regression models. It is an extension of the 'breakDown' package (Staniak and Biecek 2018) , with new and faster strategies for orderings. It supports interactions in explanations and has interactive visuals (implemented with 'D3.js' library). The methodology behind is described in the 'iBreakDown' article (Gosiewska and Biecek 2019) This package is a part of the 'DrWhy.AI' universe (Biecek 2018) .

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Install

install.packages('iBreakDown')

Monthly Downloads

4,422

Version

1.3.1

License

GPL-3

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Maintainer

Przemyslaw Biecek

Last Published

July 29th, 2020

Functions in iBreakDown (1.3.1)

describe

Generates Textual Explanations for Predictive Models
break_down

Model Agnostic Sequential Variable Attributions
plotD3.shap

Plot Shap (Break Down Uncertainty) Objects in D3 with r2d3 package.
plot.break_down_uncertainty

Plot Generic for Break Down Uncertainty Objects
break_down_uncertainty

Explanation Level Uncertainty of Sequential Variable Attribution
local_attributions

Model Agnostic Sequential Variable attributions
print.break_down

Print Generic for Break Down Objects
local_interactions

Model Agnostic Sequential Variable Attributions with Interactions
plotD3

Plot Break Down Objects in D3 with r2d3 package.
plot.break_down

Plot Generic for Break Down Objects
print.break_down_description

Print Generic for Break Down Objects
print.break_down_uncertainty

Print Generic for Break Down Uncertainty Objects