Advanced Forecasting with Python: With State-of-the-Art-Models Including LSTMs, Facebook’s Prophet, and Amazon’s DeepAR

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2021

J. KorstanjeAdvanced Forecasting with Pythonhttps://doi.org/10.1007/978-1-4842-7150-6_15

15. Gradient Boosting with XGBoost and LightGBM

Joos Korstanje¹  

(1)

Maisons Alfort, France

 

In this chapter, you will discover the gradient boosting model . In the previous chapter, you discovered the idea behind ensemble methods. As a recap, ensemble methods make powerful predictions by combining predictions of numerous small, less performant models.

Boosting: A Different Way of Ensemble Learning

Gradient boosting combines numerous small Decision Tree models to make predictions. Of course, those small decision trees are different from each other; else, there wouldn’t be ...