Edit on GitHub

XGBoost

DVCLive allows you to add experiment tracking capabilities to your XGBoost projects.

Usage

Include the DVCLiveCallback in the callbacks list passed to the xgboost.train call:

from dvclive.xgb import DVCLiveCallback

...

xgboost.train(
    param, dtrain, num_round=5, evals=[(dval, "eval_data")]
    callbacks=[DVCLiveCallback("eval_data")],
)

Parameters

  • model_file - (None by default) - The name of the file where the model will be saved at the end of each step.

  • live - (None by default) - Optional Live instance. If None, a new instance will be created using **kwargs.

  • **kwargs - Any additional arguments will be used to instantiate a new Live instance. If live is used, the arguments are ignored.

Examples

  • Using live to pass an existing Live instance.
from dvclive import Live
from dvclive.xgb import DVCLiveCallback

with Live("custom_dir") as live:
    xgboost.train(
        param,
        dtrain,
        num_round=5,
        callbacks=[DVCLiveCallback("eval_data", live=live)],
        evals=[(dval, "eval_data")])

    # Log additional metrics after training
    live.log_metric("summary_metric", 1.0, plot=False)
  • Using **kwargs to customize Live.
xgboost.train(
    param,
    dtrain,
    num_round=5,
    callbacks=[
      DVCLiveCallback(
        "eval_data",
        dir="custom_dir")],
    evals=[(dval, "eval_data")])
Content

🐛 Found an issue? Let us know! Or fix it:

Edit on GitHub

Have a question? Join our chat, we will help you:

Discord Chat