OTE: 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.

Version: 1.0
Imports: randomForest, stats
Published: 2015-07-31
Author: Zardad Khan, Asma Gul, Aris Perperoglou, Osama Mahmoud, Werner Adler, Miftahuddin and Berthold Lausen
Maintainer: Zardad Khan <zkhan at essex.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: OTE results


Reference manual: OTE.pdf
Package source: OTE_1.0.tar.gz
Windows binaries: r-devel: OTE_1.0.zip, r-release: OTE_1.0.zip, r-oldrel: OTE_1.0.zip
OS X Mavericks binaries: r-release: OTE_1.0.tgz, r-oldrel: OTE_1.0.tgz


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