GAMens

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.