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 |