Gradient Boosting Classifier

Gradient Boosting Classifier combines many simple decision trees in a step-by-step process. Each tree learns from the mistakes made by the previous trees, gradually improving prediction accuracy.

This makes it one of the most powerful classification algorithms available.

Gradient Boosting is works well even when the relationship between features and the target variable is complex or non-linear.

Use Cases

• Building type classification: Classify buildings based on geometric and spatial features (area, perimeter, orientation).
• Material prediction: Predict the most suitable material for a structural element based on its properties.
• Space usage classification: Classify rooms by their function using shape and area characteristics.