ExplainPrediction: Explanation of Predictions for Classification and Regression Models

Generates explanations for classification and regression models and visualizes them. Explanations are generated for individual predictions as well as for models as a whole. Two explanation methods are included, EXPLAIN and IME. The EXPLAIN method is fast but might miss explanations expressed redundantly in the model. The IME method is slower as it samples from all feature subsets. For the EXPLAIN method see Robnik-Sikonja and Kononenko (2008) <doi:10.1109/TKDE.2007.190734>, and the IME method is described in Strumbelj and Kononenko (2010, JMLR, vol. 11:1-18). All models in package 'CORElearn' are natively supported, for other prediction models a wrapper function is provided and illustrated for models from packages 'randomForest', 'nnet', and 'e1071'.

Version: 1.2.3
Imports: CORElearn (≥ 1.50.3), semiArtificial (≥ 2.2.5)
Suggests: nnet, e1071, randomForest
Published: 2017-11-22
Author: Marko Robnik-Sikonja
Maintainer: Marko Robnik-Sikonja <marko.robnik at fri.uni-lj.si>
License: GPL-3
URL: http://lkm.fri.uni-lj.si/rmarko/software/
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: ExplainPrediction results

Downloads:

Reference manual: ExplainPrediction.pdf
Package source: ExplainPrediction_1.2.3.tar.gz
Windows binaries: r-devel: ExplainPrediction_1.2.3.zip, r-release: ExplainPrediction_1.2.3.zip, r-oldrel: ExplainPrediction_1.2.3.zip
OS X El Capitan binaries: r-release: ExplainPrediction_1.2.3.tgz
OS X Mavericks binaries: r-oldrel: ExplainPrediction_1.2.3.tgz
Old sources: ExplainPrediction archive

Reverse dependencies:

Reverse suggests: CORElearn

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