GAMens: Applies GAMbag, GAMrsm and GAMens ensemble classifiers for binary classification

This package implements the GAMbag, GAMrsm and GAMens ensemble classifiers for binary classification (De Bock et al., 2010). The ensembles implement Bagging (Breiman, 1996), the Random Subspace Method (Ho, 1998), 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.

Downloads:

Reverse dependencies: