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.
- Version0.1.0
- R versionunknown
- LicenseApache License (== 2.0)
- Needs compilation?No
- Last release01/24/2022
Documentation
Team
Erin LeDell
Mark van der Laan
Show author detailsRolesAuthorStephanie Sapp
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Last 30 days
This package has been downloaded 182 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 9 times.
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Last 365 days
This package has been downloaded 2,835 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 36 downloads.
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- Depends1 package
- Suggests25 packages