Other packages > Find by keyword >

subsemble  

An Ensemble Method for Combining Subset-Specific Algorithm Fits
View on CRAN: Click here


Download and install subsemble package within the R console
Install from CRAN:
install.packages("subsemble")

Install from Github:
library("remotes")
install_github("cran/subsemble")

Install by package version:
library("remotes")
install_version("subsemble", "0.1.0")



Attach the package and use:
library("subsemble")
Maintained by
Erin LeDell
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-06-28
Latest Update: 2022-01-24
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) <doi:10.1080/02664763.2013.864263>.
How to cite:
Erin LeDell (2014). subsemble: An Ensemble Method for Combining Subset-Specific Algorithm Fits. R package version 0.1.0, https://cran.r-project.org/web/packages/subsemble. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.0.8 (2014-06-28 20:57), 0.0.9 (2014-07-01 09:37)
Other packages that cited subsemble R package
View subsemble citation profile
Other R packages that subsemble depends, imports, suggests or enhances
Complete documentation for subsemble
Functions, R codes and Examples using the subsemble R package
Some associated functions: predict.subsemble . subsemble-package . subsemble . 
Some associated R codes: control.R . predict.subsemble.R . subsemble.R . zzz.R .  Full subsemble package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

composits  
Compositional, Multivariate and Univariate Time Series Outlier Ensemble
A compositional multivariate and univariate time series outlier ensemble.It uses the four R packages ...
Download / Learn more Package Citations See dependency  
dmlalg  
Double Machine Learning Algorithms
Implementation of double machine learning (DML) algorithms in R, based on Emmenegger and Buehlmann ...
Download / Learn more Package Citations See dependency  
Rfast2  
A Collection of Efficient and Extremely Fast R Functions II
A collection of fast statistical and utility functions for data analysis. Functions for regression, ...
Download / Learn more Package Citations See dependency  
LOGANTree  
Tree-Based Models for the Analysis of Log Files from Computer-Based Assessments
Enables researchers to model log-file data from computer-based assessments using machine-learning te ...
Download / Learn more Package Citations See dependency  
Maintainer: Qi Qin (view profile)
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
elect  
Estimation of Life Expectancies Using Multi-State Models
Functions to compute state-specific and marginal life expectancies. The computation is based on a fi ...
Download / Learn more Package Citations See dependency  

23,394

R Packages

201,798

Dependencies

63,416

Author Associations

23,395

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA