GAMens
Applies GAMbag, GAMrsm and GAMens Ensemble Classifiers for Binary Classification
Implements the GAMbag, GAMrsm and GAMens ensemble classifiers for binary classification doi:10.1016/j.csda.2009.12.013. The ensembles implement Bagging doi:10.1023/A:1010933404324, the Random Subspace Method 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.
- Version1.2.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release04/05/2018
Team
Koen W. De Bock, Kristof Coussement and Dirk Van den Poel
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