subsemble: An Ensemble Method for Combining Subset-Specific Algorithm Fits

Subsemble is a general subset ensemble prediction method, which can be used for small, moderate, or large datasets. Subsemble partitions the full dataset into subsets of observations, fits a specified underlying algorithm on each subset, and uses a unique form of V-fold cross-validation to output a prediction function that combines the subset-specific fits. An oracle result provides a theoretical performance guarantee for Subsemble.

Version: 0.0.9
Depends: R (≥ 2.14.0), SuperLearner
Suggests: arm, caret, class, e1071, earth, gam, gbm, glmnet, Hmisc, ipred, lattice, LogicReg, MASS, mda, mlbench, nnet, parallel, party, polspline, quadprog, randomForest, rpart, SIS, spls, stepPlr
Published: 2014-07-01
Author: Erin LeDell, Stephanie Sapp, Mark van der Laan
Maintainer: Erin LeDell <ledell at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: subsemble results


Reference manual: subsemble.pdf
Package source: subsemble_0.0.9.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: subsemble_0.0.9.tgz
OS X Mavericks binaries: r-oldrel: subsemble_0.0.9.tgz
Old sources: subsemble archive


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