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subsemble (version 0.1.0)

An Ensemble Method for Combining Subset-Specific Algorithm Fits

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) .

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install.packages('subsemble')

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211

Version

0.1.0

License

Apache License (== 2.0)

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Last Published

January 24th, 2022

Functions in subsemble (0.1.0)

subsemble

An Ensemble Method for Combining Subset-Specific Algorithm Fits
predict.subsemble

Predict method for a 'subsemble' object.
subsemble-package

An Ensemble Method for Combining Subset-Specific Algorithm Fits