Classification Trees with Imprecise Probabilities
Classification with Imprecise Probabilities
imptree: Classification Trees with Imprecise Probabilities
Classification Trees with Imprecise Probabilities
Control parameters for generating imptree objects
Method parameters for generating imptree objects
Classification with Imprecise Probabilities
Classification with Imprecise Probabilities
Classification with Imprecise Probabilities
Various method around IPIntervals
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.