snowflake.ml.experiment.callback.xgboost.SnowflakeXgboostCallback

class snowflake.ml.experiment.callback.xgboost.SnowflakeXgboostCallback(*args: Any, **kwargs: Any)

Bases: TrainingCallback

XGBoost callback for automatically logging to a Snowflake ML Experiment.

Initialize the callback.

Parameters:

  • experiment_tracking (ExperimentTracking) – The Experiment Tracking instance to use for logging.

  • log_model (bool) – Whether to log the model at the end of training. Default is True.

  • log_metrics (bool) – Whether to log metrics during training. Default is True.

  • log_params (bool) – Whether to log model parameters at the start of training. Default is True.

  • log_every_n_epochs (int) – Frequency with which to log metrics. Must be positive. Default is 1, logging after every iteration.

  • model_name (Optional[str]) – The model name to use when logging the model. If None, the model name will be derived from the experiment name.

  • version_name (Optional[str]) – The model version name to use when logging the model. If None, the version name will be randomly generated.

  • model_signature (Optional[ModelSignature]) – The model signature to use when logging the model. This is required if log_model is set to True.

Raises:

ValueError – When log_every_n_epochs is not a positive integer.

Methods

after_iteration(model: Any, epoch: int, evals_log: dict[str, dict[str, Any]]) → bool
after_training(model: xgboost.Booster) → xgboost.Booster
before_training(model: xgboost.Booster) → xgboost.Booster
Language: English