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

Ensemble classifiers based upon generalized additive models 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:1018054314350>), the Random Subspace Method (Ho (1998) <doi:10.1109/34.709601>), or both, and use Hastie and Tibshirani's (1990) 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
Depends: R (≥ 2.4.0), splines, gam, mlbench, caTools
Published: 2016-03-02
Author: Koen W. De Bock, Kristof Coussement and Dirk Van den Poel
Maintainer: Koen W. De Bock <K.DeBock at ieseg.fr>
BugReports: NA
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: NA
NeedsCompilation: no
CRAN checks: GAMens results

Downloads:

Reference manual: GAMens.pdf
Package source: GAMens_1.2.tar.gz
Windows binaries: r-devel: GAMens_1.2.zip, r-release: GAMens_1.2.zip, r-oldrel: GAMens_1.2.zip
OS X Mavericks binaries: r-release: GAMens_1.2.tgz, r-oldrel: GAMens_1.2.tgz
Old sources: GAMens archive