An Ensemble Method for Combining Subset-Specific Algorithm Fits

Description

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.

Details

Package: subsemble
Type: Package
Version: 0.0.9
Date: 2014-07-01
License: GPL (>= 2)

Author(s)

Author: Erin LeDell, Stephanie Sapp, Mark van der Laan

Maintainer: Erin LeDell <ledell@berkeley.edu>

References

Stephanie Sapp, Mark J. van der Laan & John Canny, Journal of Applied Statistics (2013). Subsemble: An ensemble method for combining subset-specific algorithm fits
http://www.tandfonline.com/doi/abs/10.1080/02664763.2013.864263
https://biostats.bepress.com/ucbbiostat/paper313

See Also

SuperLearner