Gradient Boosting Regressor

Gradient Boosting Regressor builds sequential decision trees where each new tree corrects the prediction errors of the previous ones. It predicts continuous numerical values with high accuracy.

This sequential correction process makes it one of the most powerful regression methods, especially for complex non-linear relationships.

Use Cases

• Area prediction: Predict the area of a geometry based on its perimeter, bounding box, and other spatial features.
• Energy performance estimation: Estimate building energy consumption based on geometric and spatial characteristics.
• Cost estimation: Predict construction costs based on geometric measurements of building elements.