XGBoost Linear© is an advanced implementation of a gradient boosting algorithm with a linear model as the base model. Boosting algorithms iteratively learn weak classifiers and then add them to a final strong classifier. The XGBoost Linear node in watsonx.ai Studio is implemented in Python.

For more information about boosting algorithms, see the XGBoost Tutorials. ¹

Note that the XGBoost cross-validation function is not supported in watsonx.ai Studio. You can use the Partition node for this functionality. Also note that XGBoost in watsonx.ai Studio performs one-hot encoding automatically for categorical variables.

¹ "XGBoost Tutorials." Scalable and Flexible Gradient Boosting. Web. © 2015-2016 DMLC.