no code implementations • 11 May 2023 • Guilherme Dean Pelegrina, Miguel Couceiro, Leonardo Tomazeli Duarte
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.
1 code implementation • 3 Nov 2022 • Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, Michel Grabisch
Besides accuracy, recent studies on machine learning models have been addressing the question on how the obtained results can be interpreted.
1 code implementation • 9 Sep 2022 • Guilherme Dean Pelegrina, Sajid Siraj
In this paper, we propose the use of Shapley values to explain the contribution of each feature towards the model's robustness, measured in terms of Receiver-operating Characteristics (ROC) curve and the Area under the ROC curve (AUC).
1 code implementation • 24 Aug 2022 • Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte
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.
no code implementations • 6 Feb 2020 • Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, João Marcos Travassos Romano
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.