Description: Gradient boosting regression sequentially builds models to improve predictions by correcting errors made by previous models.
Key Points:
- Highly accurate and efficient.
- Can handle different types of data.
- Prone to overfitting if not properly tuned.
Applications: Housing price prediction, customer lifetime value prediction, demand forecasting.