Learning Vector Quantization: generalization ability and dynamics of competing prototypes

Witoelar A, Biehl M, Hammer B (2007)
In: Proceedings of 6th International Workshop on Self-Organizing Maps. Bielefeld: Bielefeld University.

Konferenzbeitrag | Veröffentlicht | Englisch
 
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Autor*in
Witoelar, Aree; Biehl, Michael; Hammer, BarbaraUniBi
Abstract / Bemerkung
Learning Vector Quantization (LVQ) are popular multi-class classification algorithms. Prototypes in an LVQ system represent the typical features of classes in the data. Frequently multiple prototypes are employed for a class to improve the representation of variations within the class and the generalization ability. In this paper, we investigate the dynamics of LVQ in an exact mathematical way, aiming at understanding the influence of the number of prototypes and their assignment to classes. The theory of on-line learning allows a mathematical description of the learning dynamics in model situations. We demonstrate using a system of three prototypes the different behaviors of LVQ systems of multiple prototype and single prototype class representation.
Erscheinungsjahr
2007
Titel des Konferenzbandes
Proceedings of 6th International Workshop on Self-Organizing Maps
Konferenz
WSOM 2007
Konferenzort
Bielefeld, Germany
Konferenzdatum
2007-09-03 – 2007-09-06
ISBN
978-3-00-022473-7
Page URI
https://pub.uni-bielefeld.de/record/1994295

Zitieren

Witoelar A, Biehl M, Hammer B. Learning Vector Quantization: generalization ability and dynamics of competing prototypes. In: Proceedings of 6th International Workshop on Self-Organizing Maps. Bielefeld: Bielefeld University; 2007.
Witoelar, A., Biehl, M., & Hammer, B. (2007). Learning Vector Quantization: generalization ability and dynamics of competing prototypes. Proceedings of 6th International Workshop on Self-Organizing Maps Bielefeld: Bielefeld University. https://doi.org/10.2390/biecoll-wsom2007-126
Witoelar, A., Biehl, M., and Hammer, B. (2007). “Learning Vector Quantization: generalization ability and dynamics of competing prototypes” in Proceedings of 6th International Workshop on Self-Organizing Maps (Bielefeld: Bielefeld University).
Witoelar, A., Biehl, M., & Hammer, B., 2007. Learning Vector Quantization: generalization ability and dynamics of competing prototypes. In Proceedings of 6th International Workshop on Self-Organizing Maps. Bielefeld: Bielefeld University.
A. Witoelar, M. Biehl, and B. Hammer, “Learning Vector Quantization: generalization ability and dynamics of competing prototypes”, Proceedings of 6th International Workshop on Self-Organizing Maps, Bielefeld: Bielefeld University, 2007.
Witoelar, A., Biehl, M., Hammer, B.: Learning Vector Quantization: generalization ability and dynamics of competing prototypes. Proceedings of 6th International Workshop on Self-Organizing Maps. Bielefeld University, Bielefeld (2007).
Witoelar, Aree, Biehl, Michael, and Hammer, Barbara. “Learning Vector Quantization: generalization ability and dynamics of competing prototypes”. Proceedings of 6th International Workshop on Self-Organizing Maps. Bielefeld: Bielefeld University, 2007.

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