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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>.

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 subsemble_0.1.0.tar.gz 50.7 KiB
0.1.0 rolling linux/noble R-4.5 subsemble_0.1.0.tar.gz 50.6 KiB
0.1.0 rolling source/ R- subsemble_0.1.0.tar.gz 14.3 KiB
0.1.0 latest linux/jammy R-4.5 subsemble_0.1.0.tar.gz 50.7 KiB
0.1.0 latest linux/noble R-4.5 subsemble_0.1.0.tar.gz 50.6 KiB
0.1.0 latest source/ R- subsemble_0.1.0.tar.gz 14.3 KiB
0.1.0 2026-04-26 source/ R- subsemble_0.1.0.tar.gz 14.3 KiB
0.1.0 2026-04-23 source/ R- subsemble_0.1.0.tar.gz 14.3 KiB
0.1.0 2026-04-09 windows/windows R-4.5 subsemble_0.1.0.zip 52.5 KiB
0.1.0 2025-04-20 source/ R- subsemble_0.1.0.tar.gz 14.3 KiB

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