imptree: Classification Trees with Imprecise Probabilities

Creation of imprecise classification trees. They rely on probability estimation within each node by means of either the imprecise Dirichlet model or the nonparametric predictive inference approach. The splitting variable is selected by the strategy presented in Fink and Crossman (2013) <http://www.sipta.org/isipta13/index.php?id=paper&paper=014.html>, but also the original imprecise information gain of Abellan and Moral (2003) <doi:10.1002/int.10143> is covered.

Version: 0.5.1
Imports: Rcpp (≥ 0.12.5)
LinkingTo: Rcpp
Suggests: testthat
Published: 2018-08-17
Author: Paul Fink [aut, cre]
Maintainer: Paul Fink <paul.fink at stat.uni-muenchen.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: C++11
Materials: ChangeLog
CRAN checks: imptree results

Documentation:

Reference manual: imptree.pdf

Downloads:

Package source: imptree_0.5.1.tar.gz
Windows binaries: r-devel: imptree_0.5.1.zip, r-release: imptree_0.5.1.zip, r-oldrel: imptree_0.5.1.zip
macOS binaries: r-release (arm64): imptree_0.5.1.tgz, r-oldrel (arm64): imptree_0.5.1.tgz, r-release (x86_64): imptree_0.5.1.tgz, r-oldrel (x86_64): imptree_0.5.1.tgz

Linking:

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