# XGBoost Linear node

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 SPSS® Modeler is implemented in Python.

For more information about boosting algorithms, see the XGBoost Tutorials
available at http://xgboost.readthedocs.io/en/latest/tutorials/index.html.
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Note that the XGBoost cross-validation function is not supported in SPSS Modeler. You can use the SPSS Modeler Partition node for this functionality. Also note that XGBoost in SPSS Modeler performs one-hot encoding automatically for categorical variables.

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