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
Insights
Last 30 days
This package has been downloaded 416 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 5,870 times in the last 365 days. That's a lot of interest! Someone might even write a blog post about it. The day with the most downloads was Sep 11, 2024 with 58 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports5 packages
- Suggests1 package