gbts

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.

Last 30 days

This package has been downloaded 372 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1 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 5,848 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do 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.