Recent applications of network theory to brain networks as well as the expanding empirical databases of brain architecture spawn an interest in novel techniques for analyzing connectivity patterns in the brain. Treating individual brain structures as nodes in a directed graph model permits the application of graph theoretical concepts to the analysis of these structures within their large-scale...

• A new global eXplainable Artificial Intelligence method is proposed. Our based on the use of Shapley values and Lorenz Zonoid decomposition. The derived variable importance criterion fulfills explainability requirement. application to bitcoin data shows above mentioned advantages. Explainability artificial intelligence methods has become a crucial issue, especially in most regulated fields, s...

The asymptotic value, introduced by Kannai in 1966, is an asymptotic approach to the notion of the Shapley value for games with infinitely many players. A vector measure game is a game v where the worth v(S) of a coalition S is a function f of μ(S) where μ is a vector measure. Special classes of vector measure games are the weighted majority games and the two-house weighted majority games where...

Abstract This paper proposes a novel approach to explain the predictions made by data-driven methods. Since such rely heavily on data used for training, explanations that convey information about how training affects are useful. The quantify different data-clusters of affect prediction. quantification is based Shapley values, concept which originates from coalitional game theory, developed fair...