XGBoost Python Feature Walkthrough
This is a collection of examples for using the XGBoost Python package.

This script demonstrate how to access the eval metrics
This script demonstrate how to access the eval metrics

Demo for accessing the xgboost eval metrics by using sklearn interface
Demo for accessing the xgboost eval metrics by using sklearn interface

Demo for using feature weight to change column sampling
Demo for using feature weight to change column sampling

Collection of examples for using sklearn interface
Collection of examples for using sklearn interface

Demo for using data iterator with Quantile DMatrix
Demo for using data iterator with Quantile DMatrix

Demo for using process_type with prune and refresh
Demo for using process_type with prune and refresh

Demo for prediction using individual trees and model slices
Demo for prediction using individual trees and model slices

Collection of examples for using xgboost.spark estimator interface
Collection of examples for using xgboost.spark estimator interface

Demo for creating customized multi-class objective function
Demo for creating customized multi-class objective function

Demo for defining a custom regression objective and metric
Demo for defining a custom regression objective and metric