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Fair Feature Selection with a Lexicographic Multi-objective Genetic Algorithm

Brookhouse, James, Freitas, Alex A. (2022) Fair Feature Selection with a Lexicographic Multi-objective Genetic Algorithm. In: Lecture Notes in Computer Science. Parallel Problem Solving from Nature – PPSN XVII. PPSN 2022. 13399. pp. 151-163. Springer ISBN 978-3-031-14720-3. (doi:10.1007/978-3-031-14721-0_11) (KAR id:96225)


There is growing interest in learning from data classifiers whose predictions are both accurate and fair, avoiding discrimination against sub-groups of people based e.g. on gender or race. This paper proposes a new Lexicographic multi-objective Genetic Algorithm for Fair Feature Selection (LGAFFS). LGAFFS selects a subset of relevant features which is optimised for a given classification algorithm, by simultaneously optimising one measure of accuracy and four measures of fairness. This is achieved by using a lexicographic multi-objective optimisation approach where the objective of optimising accuracy has higher priority over the objective of optimising the four fairness measures. LGAFFS was used to select features in a pre-processing phase for a random forest algorithm. The experiments compared LGAFFS’ performance against two feature selection approaches: (a) the baseline approach of letting the random forest algorithm use all features, i.e. no feature selection in a pre-processing phase; and (b) a Sequential Forward Selection method. The results showed that LGAFFS significantly improved fairness measures in several cases, with no significant difference regarding predictive accuracy, across all experiments.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1007/978-3-031-14721-0_11
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Funders: Leverhulme Trust (
Depositing User: Alex Freitas
Date Deposited: 16 Aug 2022 08:56 UTC
Last Modified: 04 Mar 2024 18:55 UTC
Resource URI: (The current URI for this page, for reference purposes)

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