gbts
Hyperparameter Search for Gradient Boosted Trees
An implementation of hyperparameter optimization for Gradient Boosted Trees on binary classification and regression problems. The current version provides two optimization methods: Bayesian optimization and random search. Instead of giving the single best model, the final output is an ensemble of Gradient Boosted Trees constructed via the method of ensemble selection.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2.0 |
rolling source/ R- | gbts_1.2.0.tar.gz |
53.4 KiB |
1.2.0 |
rolling linux/jammy R-4.5 | gbts_1.2.0.tar.gz |
112.2 KiB |
1.2.0 |
latest source/ R- | gbts_1.2.0.tar.gz |
53.4 KiB |
1.2.0 |
latest linux/jammy R-4.5 | gbts_1.2.0.tar.gz |
112.2 KiB |
1.2.0 |
2026-04-23 source/ R- | gbts_1.2.0.tar.gz |
53.4 KiB |
1.2.0 |
2026-04-09 windows/windows R-4.5 | gbts_1.2.0.zip |
115.5 KiB |
1.2.0 |
2025-04-20 source/ R- | gbts_1.2.0.tar.gz |
53.4 KiB |