XGBoost for Regression
Extreme Gradient Boosting (XGBoost) is an open-source library that provides an efficient and effective implementation of the gradient boosting algorithm.
Shortly after its development and initial release, XGBoost became the go-to method and often the key component in winning solutions for a range of problems in machine learning competitions.
Regression predictive modeling problems involve predicting a numerical value such as a dollar amount or a height. XGBoost can be used directly for regression predictive modeling.
In this tutorial, you will discover how to develop and evaluate XGBoost regression models in Python.
After completing this tutorial, you will know:
- XGBoost is an efficient implementation of gradient boosting that can be used for regression predictive modeling.
- How to evaluate an XGBoost