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Local Interpretable (Model-Agnostic) Visual Explanations

v1.5.13 · Jan 14, 2020 · MIT + file LICENSE

Description

Interpretability of complex machine learning models is a growing concern. This package helps to understand key factors that drive the decision made by complicated predictive model (so called black box model). This is achieved through local approximations that are either based on additive regression like model or CART like model that allows for higher interactions. The methodology is based on Tulio Ribeiro, Singh, Guestrin (2016) <doi:10.1145/2939672.2939778>. More details can be found in Staniak, Biecek (2018) <doi:10.32614/RJ-2018-072>.

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dependencies in R code

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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
NOTE r-devel-linux-x86_64-fedora-clang

dependencies in R code

Namespace in Imports field not imported from: ‘e1071’
  All declared Imports should be used.
NOTE r-devel-linux-x86_64-fedora-gcc

dependencies in R code

Namespace in Imports field not imported from: ‘e1071’
  All declared Imports should be used.

Dependency Network

Dependencies Reverse dependencies mlr dplyr breakDown data.table forestmodel shiny MASS ggplot2 gower e1071 live

Version History

new 1.5.13 Mar 10, 2026
updated 1.5.13 ← 1.5.12 diff Jan 14, 2020
updated 1.5.12 ← 1.5.11 diff Dec 17, 2019
updated 1.5.11 ← 1.5.10 diff Nov 15, 2019
updated 1.5.10 ← 1.5.9 diff Feb 27, 2019
updated 1.5.9 ← 1.5.8 diff Nov 11, 2018
updated 1.5.8 ← 1.5.7 diff Sep 23, 2018
updated 1.5.7 ← 1.5.4 diff Jun 2, 2018
updated 1.5.4 ← 1.5.3 diff May 13, 2018
updated 1.5.3 ← 1.4.2 diff May 4, 2018
new 1.4.2 Apr 2, 2018