nvflare.app_opt.xgboost.metrics_cb module

class MetricsCallback(writer: LogWriter)

Bases: TrainingCallback

after_iteration(model, epoch: int, evals_log: Dict[str, Dict[str, List[float] | List[Tuple[float, float]]]])

Run after each iteration. Returns True when training should stop.

Parameters:

• model – Eeither a Booster object or a CVPack if the cv function in xgboost is being used.

• epoch – The current training iteration.

• evals_log –

  A dictionary containing the evaluation history:

  {"data_name": {"metric_name": [0.5, ...]}}