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) <>, but also the original imprecise information gain of Abellan and Moral (2003) is covered.


Reference manual

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0.5.1 by Paul Fink, 3 years ago

Browse source code at

Authors: Paul Fink [aut, cre]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp

Suggests testthat

Linking to Rcpp

System requirements: C++11

See at CRAN