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EnsemblePenReg  

Extensible Classes and Methods for Penalized-Regression-Based Integration of Base Learners
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Download and install EnsemblePenReg package within the R console
Install from CRAN:
install.packages("EnsemblePenReg")

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

Install by package version:
library("remotes")
install_version("EnsemblePenReg", "0.7")



Attach the package and use:
library("EnsemblePenReg")
Maintained by
Alireza S. Mahani
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-11-28
Latest Update: 2016-09-14
Description:
Extending the base classes and methods of EnsembleBase package for Penalized-Regression-based (Ridge and Lasso) integration of base learners. Default implementation uses cross-validation error to choose the optimal lambda (shrinkage parameter) for the final predictor. The package takes advantage of the file method provided in EnsembleBase package for writing estimation objects to disk in order to circumvent RAM bottleneck. Special save and load methods are provided to allow estimation objects to be saved to permanent files on disk, and to be loaded again into temporary files in a later R session. Users and developers can extend the package by extending the generic methods and classes provided in EnsembleBase package as well as this package.
How to cite:
Alireza S. Mahani (2014). EnsemblePenReg: Extensible Classes and Methods for Penalized-Regression-Based Integration of Base Learners. R package version 0.7, https://cran.r-project.org/web/packages/EnsemblePenReg. Accessed 03 Dec. 2024.
Previous versions and publish date:
0.6 (2014-11-28 09:31)
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