localICE: Local Individual Conditional Expectation

Local Individual Conditional Expectation is as an extension to Individual Conditional Expectation (ICE) and provides three-dimensional local explanations for particular data instances. The three dimension are two features at the horizontal and vertical axes as well as the target that is represented by different colors. The approach is applicable for classification and regression problems to explain interactions of two features towards the target. The plot for discrete targets looks similar to plots of cluster algorithms like k-means, where different clusters represent different predictions. Reference to the ICE approach: Alex Goldstein, Adam Kapelner, Justin Bleich, Emil Pitkin (2013) <arXiv:1309.6392>.

Version: 0.1.0
Imports: ggplot2, checkmate
Suggests: covr, h2o, mlbench, randomForest, stats, testthat, utils
Published: 2019-02-01
Author: Martin Walter [aut, cre]
Maintainer: Martin Walter <mf-walter at web.de>
BugReports: https://github.com/viadee/localICE/issues
License: BSD_3_clause + file LICENSE
URL: https://github.com/viadee/localICE
NeedsCompilation: no
Materials: README
CRAN checks: localICE results


Reference manual: localICE.pdf
Package source: localICE_0.1.0.tar.gz
Windows binaries: r-devel: localICE_0.1.0.zip, r-release: localICE_0.1.0.zip, r-oldrel: localICE_0.1.0.zip
OS X binaries: r-release: localICE_0.1.0.tgz, r-oldrel: localICE_0.1.0.tgz


Please use the canonical form https://CRAN.R-project.org/package=localICE to link to this page.