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.
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