Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data

Schneider P, Biehl M, Schleif F-M, Hammer B (2007)
In: Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007). Bielefeld: Bielefeld University.

Konferenzbeitrag | Veröffentlicht | Englisch
 
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Autor*in
Schneider, Petra; Biehl, Michael; Schleif, Frank-MichaelUniBi ; Hammer, BarbaraUniBi
Abstract / Bemerkung
Metric adaptation constitutes a powerful approach to improve the performance of prototype based classication schemes. We apply extensions of Generalized LVQ based on different adaptive distance measures in the domain of clinical proteomics. The Euclidean distance in GLVQ is extended by adaptive relevance vectors and matrices of global or local influence where training follows a stochastic gradient descent on an appropriate error function. We compare the performance of the resulting learning algorithms for the classification of high dimensional mass spectrometry data from cancer research. High prediction accuracies can be obtained by adapting full matrices of relevance factors in the distance measure in order to adjust the metric to the underlying data structure. The easy interpretability of the resulting models after training of relevance vectors allows to identify discriminative features in the original spectra.
Erscheinungsjahr
2007
Titel des Konferenzbandes
Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007)
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/1994016

Zitieren

Schneider P, Biehl M, Schleif F-M, Hammer B. Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data. In: Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007). Bielefeld: Bielefeld University; 2007.
Schneider, P., Biehl, M., Schleif, F. - M., & Hammer, B. (2007). Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data. Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007) Bielefeld: Bielefeld University. https://doi.org/10.2390/biecoll-wsom2007-135
Schneider, P., Biehl, M., Schleif, F. - M., and Hammer, B. (2007). “Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data” in Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007) (Bielefeld: Bielefeld University).
Schneider, P., et al., 2007. Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data. In Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007). Bielefeld: Bielefeld University.
P. Schneider, et al., “Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data”, Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007), Bielefeld: Bielefeld University, 2007.
Schneider, P., Biehl, M., Schleif, F.-M., Hammer, B.: Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data. Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007). Bielefeld University, Bielefeld (2007).
Schneider, Petra, Biehl, Michael, Schleif, Frank-Michael, and Hammer, Barbara. “Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data”. Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007). Bielefeld: Bielefeld University, 2007.
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2021-07-26T13:33:09Z
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