View Source API Reference EXGBoost v0.5.0

Elixir bindings for the XGBoost library. EXGBoost provides an implementation of XGBoost that works with Nx tensors.

A Booster is the main object used for training and prediction. It is a wrapper around the underlying XGBoost C API. Booster have three main concepts for tracking associated data: parameters, attributes, and features. Parameters are used to configure the Booster and are from a set of valid options (such as tree_depth and eta -- refer to EXGBoost.Parameters for full list). Attributes are user-provided key-value pairs that are assigned to a Booster (such as best_iteration and best_score). Features are used to track the metadata associated with the features used in training (such as feature_names and feature_types).

Parameters are used to configure the training process and the booster.

Functions for plotting EXGBoost Booster models using Vega

Callbacks are a mechanism to hook into the training process and perform custom actions.