ModelFox Tree Benchmarks
ModelFox Tree is a pure Rust implementation of Gradient Boosted Decision Trees. It has the smallest memory footprint of the leading GBDT implementations and achieves state of the art speed and accuracy. Check it out on GitHub.
The flights dataset contains 9 columns. There are 10,000,000 rows in the train dataset and 100,000 rows in the test dataset. The target column is dep_delayed_15min and it is a binary classification task.
Training Time (lower is better)
Library | Duration | v. ModelFox |
---|---|---|
catboost | 329 sec | 9.235x |
lightgbm | 43.47 sec | 1.22x |
sklearn | 90.4 sec | 2.537x |
modelfox | 35.63 sec | 1x |
xgboost | 46.84 sec | 1.315x |
catboost
lightgbm
sklearn
modelfox
xgboost
Memory Usage (lower is better)
Library | Memory | v. ModelFox |
---|---|---|
catboost | 7.291 GB | 5.071x |
lightgbm | 2.612 GB | 1.817x |
sklearn | 2.78 GB | 1.933x |
modelfox | 1.438 GB | 1x |
xgboost | 2.88 GB | 2.003x |
catboost
lightgbm
sklearn
modelfox
xgboost
AUC (higher is better)
Library | AUC | v. ModelFox |
---|---|---|
catboost | 0.7357 | 0.9414x |
lightgbm | 0.7807 | 0.999x |
sklearn | 0.758 | 0.9699x |
modelfox | 0.7815 | 1x |
xgboost | 0.7578 | 0.9697x |
catboost
lightgbm
sklearn
modelfox
xgboost