Mitigating the Bias in Data for Fairness Using an Advanced Generalized Learning Vector Quantization Approach -- FA(IR)$^2$MA-GLVQ

We propose a bias detection and mitigating scheme for data in the context of classification tasks based on learning vector quantizers (LVQ) as classifier.For this purpose generalized LVQ endowed with an advanced matrix adaptation scheme is used for bias detection.The bias removal from data is realized applying a nullspace data projection using the adjusted matrix.The usefulness of the approach is demonstrated and illustrated in terms of two real world datasets.