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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 |
DOI: | 10.32614/CRAN.package.GAMens |
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 |
Reference manual: | GAMens.pdf |
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, r-oldrel (x86_64): GAMens_1.2.1.tgz |
Old sources: | GAMens archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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