XGBoost is a scalable and efficient gradient boosting framework for machine learning, optimized for speed and performance.
Source codeOverview
XGBoost is a powerful, scalable, and efficient gradient boosting framework used in many machine learning applications. It is widely known for its performance in structured/tabular data problems, offering implementations for regression, classification, and ranking tasks.
Usage/Documentation
XGBoost is highly optimized for both speed and accuracy. It supports a variety of interfaces, including Python, R, and Julia. For detailed instructions on how to use XGBoost, refer to the XGBoost documentation.
Installation
XGBoost can be installed using pip:
pip install xgboost
Resources
Tutorials
There is no available tutorial for this tool.