Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
The split-by-leaf mode (grow_policy="lossguide") is not supported in distributed training,
which makes XGBoost4J on Spark much slower than LightGBM on Spark.
https://towardsdatascience.com/build-xgboost-lightgbm-models-on-large-datasets-what-are-the-possible-solutions-bf882da2c27d
https://xgboost …
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
It is suggested that you use the sklearn wrapper classes XGBClassifier and XGBRegressor
so that you can fully leverage other tools of the sklearn package.
There are 2 types of boosters …
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
https://xgboost.ai/
https://machinelearningmastery.com/best-tune-multithreading-support-xgboost-python/
https://medium.com/data-design/xgboost-gpu-performance-on-low-end-gpu-vs-high-end-cpu-a7bc5fcd425b
xgboost GPU is fast. Very fast. As long as it fits in RAM and …