Model Agreement via Anchoring

Researchers developed a new mathematical technique called 'anchoring' to control model disagreement between machine learning models trained independently. The method provides bounds for reducing disagreement to zero across four common ML algorithms including stacked aggregation, gradient boosting, neural networks, and regression trees.