subsemble: An Ensemble Method for Combining Subset-Specific Algorithm Fits
The Subsemble algorithm 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 k-fold cross-validation to output a prediction function that combines the subset-specific fits. An oracle result provides a theoretical performance guarantee for Subsemble. The paper, "Subsemble: An ensemble method for combining subset-specific algorithm fits" is authored by Stephanie Sapp, Mark J. van der Laan & John Canny (2014) <doi:10.1080/02664763.2013.864263>.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.14.0),SuperLearner |
| Suggests: | arm,caret,class,cvAUC,e1071,earth,gam,gbm,glmnet,Hmisc,ipred,lattice,LogicReg,MASS,mda,mlbench,nnet, parallel,party,polspline,quadprog,randomForest,rpart,SIS,spls,stepPlr |
| Published: | 2022-01-24 |
| DOI: | 10.32614/CRAN.package.subsemble |
| Author: | Erin LeDell [cre], Stephanie Sapp [aut], Mark van der Laan [aut] |
| Maintainer: | Erin LeDell <oss at ledell.org> |
| BugReports: | https://github.com/ledell/subsemble/issues |
| License: | Apache License (== 2.0) |
| URL: | https://github.com/ledell/subsemble |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | subsemble results |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=subsembleto link to this page.