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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2.1 |
rolling source/ R- | GAMens_1.2.1.tar.gz |
9.3 KiB |
1.2.1 |
rolling linux/jammy R-4.5 | GAMens_1.2.1.tar.gz |
45.2 KiB |
1.2.1 |
latest source/ R- | GAMens_1.2.1.tar.gz |
9.3 KiB |
1.2.1 |
latest linux/jammy R-4.5 | GAMens_1.2.1.tar.gz |
45.2 KiB |
1.2.1 |
2026-04-23 source/ R- | GAMens_1.2.1.tar.gz |
9.3 KiB |
1.2.1 |
2026-04-09 windows/windows R-4.5 | GAMens_1.2.1.zip |
47.7 KiB |
1.2.1 |
2025-04-20 source/ R- | GAMens_1.2.1.tar.gz |
9.3 KiB |