localICE

0.1.1

Local Individual Conditional Expectation

0packages depend

2.3Kdownloads / year

100.0%test coverage

4/13checks pass

Overview

About

Maintained by Martin WalterFirst published 2019-02-012 releasesCRAN page ↗GitHub ↗

Local Individual Conditional Expectation ('localICE') is a local explanation approach from the field of eXplainable Artificial Intelligence (XAI). localICE is a model-agnostic XAI approach which provides three-dimensional local explanations for particular data instances. The approach is proposed in the master thesis of Martin Walter as an extension to ICE (see Reference). The three dimensions are the two features at the horizontal and vertical axes as well as the target represented by different colors. The approach is applicable for classification and regression problems to explain interactions of two features towards the target. For classification models, the number of classes can be more than two and each class is added as a different color to the plot. The given instance is added to the plot as two dotted lines according to the feature values. The localICE-package can explain features of type factor and numeric of any machine learning model. Automatically supported machine learning packages are 'mlr', 'randomForest', 'caret' or all other with an S3 predict function. For further model types from other libraries, a predict function has to be provided as an argument in order to get access to the model. Reference to the ICE approach: Alex Goldstein, Adam Kapelner, Justin Bleich, Emil Pitkin (2013) arXiv:1309.6392.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("localICE", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("viadee/localICE")

Development version from viadee/localICE. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-localice

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-localICE

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-localICE

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

9ERROR4OK

Failing flavors

ERROR r-devel-linux-x86_64-debian-clang
ERROR r-devel-linux-x86_64-debian-gcc
ERROR r-devel-linux-x86_64-fedora-clang
ERROR r-devel-linux-x86_64-fedora-gcc
ERROR r-devel-windows-x86_64
ERROR r-oldrel-windows-x86_64
ERROR r-patched-linux-x86_64
ERROR r-release-linux-x86_64
ERROR r-release-windows-x86_64

Slowest check: 1.7 min · r-oldrel-windows-x86_64

Code health

Yes

Tests · ratio 2.08

100.0%

Coverage · measured lines

100%

Documentation · exports

Dependencies · direct

Check history

ERROR2026-07-25
9 OK · 1 NOTE · 0 WARNING · 3 ERROR · 0 FAILURE
NOTE2026-03-10
7 OK · 7 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMEYes · 137 wordsVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 100%
Return-value docs: 100%
References docs: 100%

Downloads

2.3K

CRAN downloads in the past year

Rank #19,007 · ~6/day · ~188/mo

Releases R versions

Daily download trend is not available in this view yet.

19730 days

57890 days

2.3K1 year

Compare downloads with other packages →

Also on100 r2u3 autocran

Repository

GitHub ↗ viadee/localice

7Stars

0Forks

0Open issues

0Open PRs

1Releases

68Commits

2Contributors

explainable-aiairggplotvisualizationmachine-learning

68 commits · Last activity 2020-12-19 · 0% stars, 30d

Stars over time

2019-03-26 · 72026-07-07 · 7

Repository practices

Upstream repositoryBeta

3 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/viadee/localice on 2026-08-02.

Continuous integration (1)

Travis CI

Lint, format, editor (1)

RStudio project

Coverage (1)

Codecov

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

7 external dependencies (excludes base and recommended)

Depends (0)

none

Imports (2)

ggplot2 checkmate

LinkingTo (0)

none

Suggests (7)

covr h2o mlbench randomForeststatstestthatutils

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (1)

Maintainer (1)

Martin Walter

Author, Maintainer

Authors (1)

Martin Walter

Author, Maintainer

Package Timeline

2 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
R
R 4.0.0 released · 2020-04-24
0.1.1Latest
2020-02-08 · current release · diff ↗
R
R 3.6.0 released · 2019-04-26
0.1.0
2019-02-01
R
R 3.5.0 released · 2018-04-23

Package metadata

First published: 2019-02-01
Total releases: 2 / 7 yrs
License: BSD_3_clause + file LICENSE OSI
Download size: 6.9 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Report a problem with this page →