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.
- Version1.2.0
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- LicenseLICENSE
- Needs compilation?No
- Last release02/27/2017
Documentation
Team
Waley W. J. Liang
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- Imports5 packages
- Suggests1 package