FairGLVQ: Fairness in Partition-Based Classification

Störck F, Hinder F, Brinkrolf J, Paaßen B, Vaquet V, Hammer B (2024)
In: Proceedings of the 15th International Workshop on Self-Organizing Maps (WSOM 2024). Villmann T, Kaden M, Geweniger T, Schleif F-M (Eds); Cham: Springer Nature Switzerland: 141-151.

Konferenzbeitrag | Englisch
 
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Herausgeber*in
Villmann, Thomas; Kaden, Marika; Geweniger, Tina; Schleif, Frank-Michael
Abstract / Bemerkung
Fairness is an important objective throughout society. From the distribution of limited goods such as education, over hiring and payment, to taxes, legislation, and jurisprudence. Due to the increasing importance of machine learning approaches in all areas of daily life including those related to health, security, and equity, an increasing amount of research focuses on fair machine learning. In this work, we focus on the fairness of partition- and prototype-based models. The contribution of this work is twofold: 1) we develop a general framework for fair machine learning of partition-based models that does not depend on a specific fairness definition, and 2) we derive a fair version of learning vector quantization (LVQ) as a specific instantiation. We compare the resulting algorithm against other algorithms from the literature on theoretical and real-world data showing its practical relevance.
Erscheinungsjahr
2024
Titel des Konferenzbandes
Proceedings of the 15th International Workshop on Self-Organizing Maps (WSOM 2024)
Seite(n)
141-151
Konferenz
International Workshop on Self-Organizing Maps (WSOM 2024)
Konferenzort
Mittweida
Konferenzdatum
2024-07-10 – 2024-07-12
Page URI
https://pub.uni-bielefeld.de/record/2992095

Zitieren

Störck F, Hinder F, Brinkrolf J, Paaßen B, Vaquet V, Hammer B. FairGLVQ: Fairness in Partition-Based Classification. In: Villmann T, Kaden M, Geweniger T, Schleif F-M, eds. Proceedings of the 15th International Workshop on Self-Organizing Maps (WSOM 2024). Cham: Springer Nature Switzerland; 2024: 141-151.
Störck, F., Hinder, F., Brinkrolf, J., Paaßen, B., Vaquet, V., & Hammer, B. (2024). FairGLVQ: Fairness in Partition-Based Classification. In T. Villmann, M. Kaden, T. Geweniger, & F. - M. Schleif (Eds.), Proceedings of the 15th International Workshop on Self-Organizing Maps (WSOM 2024) (pp. 141-151). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-67159-3_17
Störck, Felix, Hinder, Fabian, Brinkrolf, Johannes, Paaßen, Benjamin, Vaquet, Valerie, and Hammer, Barbara. 2024. “FairGLVQ: Fairness in Partition-Based Classification”. In Proceedings of the 15th International Workshop on Self-Organizing Maps (WSOM 2024), ed. Thomas Villmann, Marika Kaden, Tina Geweniger, and Frank-Michael Schleif, 141-151. Cham: Springer Nature Switzerland.
Störck, F., Hinder, F., Brinkrolf, J., Paaßen, B., Vaquet, V., and Hammer, B. (2024). “FairGLVQ: Fairness in Partition-Based Classification” in Proceedings of the 15th International Workshop on Self-Organizing Maps (WSOM 2024), Villmann, T., Kaden, M., Geweniger, T., and Schleif, F. - M. eds. (Cham: Springer Nature Switzerland), 141-151.
Störck, F., et al., 2024. FairGLVQ: Fairness in Partition-Based Classification. In T. Villmann, et al., eds. Proceedings of the 15th International Workshop on Self-Organizing Maps (WSOM 2024). Cham: Springer Nature Switzerland, pp. 141-151.
F. Störck, et al., “FairGLVQ: Fairness in Partition-Based Classification”, Proceedings of the 15th International Workshop on Self-Organizing Maps (WSOM 2024), T. Villmann, et al., eds., Cham: Springer Nature Switzerland, 2024, pp.141-151.
Störck, F., Hinder, F., Brinkrolf, J., Paaßen, B., Vaquet, V., Hammer, B.: FairGLVQ: Fairness in Partition-Based Classification. In: Villmann, T., Kaden, M., Geweniger, T., and Schleif, F.-M. (eds.) Proceedings of the 15th International Workshop on Self-Organizing Maps (WSOM 2024). p. 141-151. Springer Nature Switzerland, Cham (2024).
Störck, Felix, Hinder, Fabian, Brinkrolf, Johannes, Paaßen, Benjamin, Vaquet, Valerie, and Hammer, Barbara. “FairGLVQ: Fairness in Partition-Based Classification”. Proceedings of the 15th International Workshop on Self-Organizing Maps (WSOM 2024). Ed. Thomas Villmann, Marika Kaden, Tina Geweniger, and Frank-Michael Schleif. Cham: Springer Nature Switzerland, 2024. 141-151.

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