Decision Trees

Combines various decision tree algorithms, plus both linear regression and ensemble methods into one package. Allows for the use of both continuous and categorical outcomes. An optional feature is to quantify the (in)stability to the decision tree methods, indicating when results can be trusted and when ensemble methods may be preferential.


Reference manual

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0.4.2 by Ross Jacobucci, 4 years ago

Browse source code at

Authors: Ross Jacobucci

Documentation:   PDF Manual  

GPL (>= 2) license

Depends on rpart, party, evtree, partykit, caret

Suggests randomForest, tree, MASS, ISLR, matrixStats, plyr, rpart.utils, stringr, pROC

See at CRAN