Gradient Boosting Trend 2026

Machine learning models often struggle with complex patterns, but Gradient Boosting tackles this by building a sequence of weak decision trees, where each new tree corrects the errors of the previous one. This iterative ensemble method delivers high predictive accuracy for regression and classification tasks. Data scientists and analysts use it for fraud detection, customer churn prediction, and ranking systems, benefiting from its robustness with structured data and minimal feature engineering.