Package: subsemble
Type: Package
Title: An Ensemble Method for Combining Subset-Specific Algorithm Fits
Version: 0.1.0
Date: 2022-01-22
Authors@R: c(
    person("Erin", "LeDell", email = "oss@ledell.org", role = "cre"),
    person("Stephanie", "Sapp", role = "aut"),
    person("Mark", "van der Laan", role = c("aut")))
Description: 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>. 
License: Apache License (== 2.0)
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
URL: https://github.com/ledell/subsemble
BugReports: https://github.com/ledell/subsemble/issues
LazyLoad: yes
NeedsCompilation: no
Packaged: 2022-01-21 07:40:07 UTC; me
Author: Erin LeDell [cre],
  Stephanie Sapp [aut],
  Mark van der Laan [aut]
Maintainer: Erin LeDell <oss@ledell.org>
Repository: CRAN
Date/Publication: 2022-01-24 20:10:02 UTC
Built: R 4.6.0; ; 2026-04-26 04:58:58 UTC; unix
