XGBoost is a popular gradient boosting library that is widely used in machine learning tasks. It provides a powerful set of features, including the ability to define custom callback functions.

Callback functions in XGBoost allow you to execute custom code at specific stages during the training process. This can be useful for tasks such as early stopping, model checkpointing, or custom metric evaluation.

In this blog post, we will explore how to define and use custom callback functions in XGBoost using Python.

Defining a Custom Callback Function

To define a custom callback function in XGBoost, you need to create a subclass of the xgboost.callback.TrainingCallback class and override the relevant methods. The TrainingCallback class provides several methods that you can override to perform different actions at different stages during training.

Here’s an example of a custom callback function that prints the training progress at each boosting round:

import xgboost as xgb

class CustomCallback(xgb.callback.TrainingCallback):
    def before_iteration(self, model, epoch, evals_log):
        print(f"Training iteration {epoch+1}")

xgb.train(params, dtrain, num_boost_round=10, callbacks=[CustomCallback()])

In this example, the before_iteration method is overridden to print the current training iteration. You can customize this method to perform any desired action, such as logging metrics, saving checkpoints, or updating progress bars.

Using the Custom Callback Function

To use the defined custom callback function during training, you need to pass it as a parameter to the xgboost.train function using the callbacks argument. In the example above, we pass an instance of CustomCallback as the value for the callbacks argument.

xgb.train(params, dtrain, num_boost_round=10, callbacks=[CustomCallback()])

You can also pass multiple callbacks by providing a list of callback instances.

xgb.train(params, dtrain, num_boost_round=10, callbacks=[CustomCallback(), AnotherCallback()])

Conclusion

Custom callback functions in XGBoost provide a flexible way to execute custom code at specific stages during the training process. By defining and using custom callback functions, you can enhance the functionality of XGBoost and tailor it to your specific requirements.

Remember to explore the official XGBoost documentation for more information on available callback methods and their usage.

Happy boosting!