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Found 6 papers, 3 papers with code
Multicriteria decision support employing adaptive prediction in a tensor-based feature representation
More specifically, we structure the criteria' past data as a tensor and, by applying adaptive prediction, we compose signals with these prediction values of the criteria.
A statistical approach to detect sensitive features in a group fairness setting
However, such an approach is subjective and does not guarantee that these features are the only ones to be considered as sensitive nor that they entail unfair (disparate) outcomes.
A $k$-additive Choquet integral-based approach to approximate the SHAP values for local interpretability in machine learning
Besides accuracy, recent studies on machine learning models have been addressing the question on how the obtained results can be interpreted.
A novel approach for Fair Principal Component Analysis based on eigendecomposition
Principal component analysis (PCA), a ubiquitous dimensionality reduction technique in signal processing, searches for a projection matrix that minimizes the mean squared error between the reduced dataset and the original one.
Identification of Choquet capacity in multicriteria sorting problems through stochastic inverse analysis
In multicriteria decision aiding (MCDA), the Choquet integral has been used as an aggregation operator to deal with the case of interacting decision criteria.
Application of independent component analysis and TOPSIS to deal with dependent criteria in multicriteria decision problems
A vast number of multicriteria decision making methods have been developed to deal with the problem of ranking a set of alternatives evaluated in a multicriteria fashion.
