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 berkeley.edu> |
| 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: subsemble_0.0.9.zip, r-release: subsemble_0.0.9.zip, r-oldrel: subsemble_0.0.9.zip |
| OS X binaries: | r-release: subsemble_0.0.9.tgz, r-oldrel: subsemble_0.0.9.tgz |
| Old sources: | subsemble archive |
Please use the canonical form https://CRAN.R-project.org/package=subsemble to link to this page.