GAMens: Applies GAMbag, GAMrsm and GAMens Ensemble Classifiers for Binary Classification

Implements the GAMbag, GAMrsm and GAMens ensemble classifiers for binary classification (De Bock et al., 2010) <doi:10.1016/j.csda.2009.12.013>. The ensembles implement Bagging (Breiman, 1996) <doi:10.1023/A:1010933404324>, the Random Subspace Method (Ho, 1998) <doi:10.1109/34.709601> , or both, and use Hastie and Tibshirani's (1990, ISBN:978-0412343902) generalized additive models (GAMs) as base classifiers. Once an ensemble classifier has been trained, it can be used for predictions on new data. A function for cross validation is also included.

Version: 1.2.1
Depends: R (≥ 2.4.0), splines, gam, mlbench, caTools
Published: 2018-04-05
Author: Koen W. De Bock, Kristof Coussement and Dirk Van den Poel
Maintainer: Koen W. De Bock <kdebock at audencia.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: GAMens results

Documentation:

Reference manual: GAMens.pdf

Downloads:

Package source: GAMens_1.2.1.tar.gz
Windows binaries: r-devel: GAMens_1.2.1.zip, r-release: GAMens_1.2.1.zip, r-oldrel: GAMens_1.2.1.zip
macOS binaries: r-release (arm64): GAMens_1.2.1.tgz, r-oldrel (arm64): GAMens_1.2.1.tgz, r-release (x86_64): GAMens_1.2.1.tgz
Old sources: GAMens archive

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