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.
Package details |
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Author | Koen W. De Bock, Kristof Coussement and Dirk Van den Poel |
Maintainer | Koen W. De Bock <kdebock@audencia.com> |
License | GPL (>= 2) |
Version | 1.2.1 |
Package repository | View on CRAN |
Installation |
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