EnsemblePCReg: Extensible Package for Principal-Component-Regression-Based Integration of Base Learners

Extends the base classes and methods of EnsembleBase package for Principal-Components-Regression-based (PCR) integration of base learners. Default implementation uses cross-validation error to choose the optimal number of PC components 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.

Version: 1.0.0
Depends: EnsembleBase
Imports: parallel, methods
Suggests: R.rsp
Published: 2016-02-13
Author: Mansour T.A. Sharabiani, Alireza S. Mahani
Maintainer: Alireza S. Mahani <alireza.mahani at sentrana.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: EnsemblePCReg results

Downloads:

Reference manual: EnsemblePCReg.pdf
Vignettes: EnsemblePCReg: An R package for fully-automated ensemble learning with reproducible prediction using Principal Components Regression
Package source: EnsemblePCReg_1.0.0.tar.gz
Windows binaries: r-devel: EnsemblePCReg_1.0.0.zip, r-release: EnsemblePCReg_1.0.0.zip, r-oldrel: EnsemblePCReg_1.0.0.zip
OS X Snow Leopard binaries: r-release: EnsemblePCReg_1.0.0.tgz, r-oldrel: EnsemblePCReg_0.6.tgz
OS X Mavericks binaries: r-release: EnsemblePCReg_1.0.0.tgz
Old sources: EnsemblePCReg archive