Shapley Values: A Comparison of Definitions and Approximation Methods

The Shapley value method is an explanatory method that describes the feature attribution of Machine Learning models. There are three different definitions of the Shapley values, namely Conditional Expectation Shapley, Marginal Expectation Shapley and Baseline Shapley. A comparison is made between the three definitions and they are applied to one...

Efficient Shapley Value Approximation Methods: for Cost Redistribution in Energy Communities

With the emergence of energy communities, where a number of prosumers (consumers with their own energy generation) invest in shared renewable generation capacity and battery storage, the issue of fair allocation of benefits and costs has become increasingly important. The Shapley value, a solution concept in cooperative game theory initially...

Uncovering taste heterogeneity and non-linearity for urban mode choice using SHAP

European cities are implementing diverse strategies to curtail car usage. Understanding the impact of these policies necessitates insights into mode choice behaviour. However, for conventional discrete choice models, utility specifications must be defined upfront, potentially leading to misleading policy recommendations. This problem is solved...