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XGBoost Plugins Modules

This folder contains plugin modules to xgboost that can be optionally installed. The plugin system helps us to extend xgboost with additional features, and add experimental features that may not yet be ready to be included in the main project.

To include a certain plugin, say plugin_a, you only need to add the following line to the

# Add plugin by including the plugin in
XGB_PLUGINS += plugin/plugin_a/

Then rebuild libxgboost by typing make, you can get a new library with the plugin enabled.

Link Static XGBoost Library with Plugins

This problem only happens when you link libxgboost.a. If you only use include python and other bindings), you can ignore this section.

When you want to link libxgboost.a with additional plugins included, you will need to enabled whole archive via The following option.

--whole-archive libxgboost.a --no-whole-archive

Write Your Own Plugin

You can plugin your own modules to xgboost by adding code to this folder, without modification to the main code repo. The example folder provides an example to write a plugin.

List of register functions

A plugin has to register a new functionality to xgboost to be able to use it. The register macros available to plugin writers are:

  • XGBOOST_REGISTER_METRIC - Register an evaluation metric
  • XGBOOST_REGISTER_GBM - Register a new gradient booster that learns through gradient statistics
  • XGBOOST_REGISTER_OBJECTIVE - Register a new objective function used by xgboost
  • XGBOOST_REGISTER_TREE_UPDATER - Register a new tree-updater which updates the tree given the gradient information

And from dmlc-core:

  • DMLC_REGISTER_PARAMETER - Register a set of parameter for a specific usecase
  • DMLC_REGISTER_DATA_PARSER - Register a data parser where the data can be represented by a URL. This is used by DMatrix.