Optimal Trees Ensembles for Regression, Classification and Class Membership Probability Estimation

Functions for creating ensembles of optimal trees for regression, classification and class membership probability estimation are given. A few trees are selected from an initial set of trees grown by random forest for the ensemble on the basis of their individual and collective performance. Trees are assessed on out-of-bag data and on an independent training data set for individual and collective performance respectively. The prediction functions return estimates of the test responses and their class membership probabilities. Unexplained variations, error rates, confusion matrix, Brier scores, etc. are also returned for the test data.


Reference manual

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1.0 by Zardad Khan, 4 years ago

Browse source code at https://github.com/cran/OTE

Authors: Zardad Khan , Asma Gul , Aris Perperoglou , Osama Mahmoud , Werner Adler , Miftahuddin and Berthold Lausen

Documentation:   PDF Manual  

GPL (>= 2) license

Imports randomForest, stats

See at CRAN