iAdditive: fast and fair Shapley-inspired feature attribution for correlated features
Interpreting machine learning models fairly and efficiently remains challenging, particularly when features are correlated. Classical Shapley-based explanations can split attribution among substitutes and are often computationally demanding. This study presents iAdditive, a model-agnostic approach that promotes fairnes...