CRAN/E | subsemble

subsemble

An Ensemble Method for Combining Subset-Specific Algorithm Fits

Installation

About

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.

github.com/ledell/subsemble
Bug report File report

Key Metrics

Version 0.1.0
R ≥ 2.14.0
Published 2022-01-24 817 days ago
Needs compilation? no
License Apache License (== 2.0)
CRAN checks subsemble results

Downloads

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Maintainer

Maintainer

Erin LeDell

oss@ledell.org

Authors

Erin LeDell

cre

Stephanie Sapp

aut

Mark van der Laan

aut

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

subsemble archive

Depends

R ≥ 2.14.0
SuperLearner

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