Federated XGBoost¶
Overview¶
NVFlare supports federated learning using popular gradient boosting library XGBoost. It uses XGBoost library with federated plugin (xgboost version >= 1.7.0rc1) to perform the learning.
Using XGBoost with NVFlare has following benefits compared with running federated XGBoost directly,
XGBoost instance’s life-cycle is managed by NVFlare. Both XGBoost client and server are started/stopped automatically by NVFlare workflow.
For histogram-based XGBoost federated server can be configured automatically with auto-assigned port number.
When mutual TLS is used, the certificates are managed by NVFlare using existing provisioning process.
No need to manually configure each instance. Instance specific parameters like code:rank are assigned automatically by the NVFlare controller.
Examples¶
Basic components to run XGBoost are already included with NVFlare distribution. Most XGBoost jobs can be created without custom code.
Please refer to NVFlare/examples/advanced/xgboost for more details.