An Incremental On-line Classifier for Imbalanced, Incomplete, and Noisy Data

Tscherepanow M, Riechers S (2012)
In: Proceedings of the ECAI Workshop on Active and Incremental Learning (AIL). Lemaire V, Lamirel J-C, Cuxac P (Eds); 18-23.

Konferenzbeitrag | Veröffentlicht| Englisch
 
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Autor/in
Tscherepanow, MarkoUniBi; Riechers, Sören
Herausgeber*in
Lemaire, Vincent; Lamirel, Jean-Charles; Cuxac, Pascal
Abstract / Bemerkung
Incremental on-line learning is a research topic gaining increasing interest in the machine learning community. Such learning methods are highly adaptive, not restricted to distinct training and application phases, and applicable to large volumes of data. In this paper, we present a novel classifier based on the unsupervised topology-learning TopoART neural network. We demonstrate that this classifier is capable of fast incremental on-line learning and achieves excellent results on standard datasets. We further show that it can successfully process imbalanced, incomplete, and noisy data. Due to these properties, we consider it a promising component for constructing artificial agents operating in real-world environments.
Stichworte
TopoART; on-line learning; incremental learning; Adaptive Resonance Theory; classification
Erscheinungsjahr
2012
Titel des Konferenzbandes
Proceedings of the ECAI Workshop on Active and Incremental Learning (AIL)
Seite(n)
18-23
Konferenz
European Conference on Artificial Intelligence (ECAI), Workshop on Active and Incremental Learning (AIL)
Konferenzort
Montpellier, France
Konferenzdatum
2012-08-27
Page URI
https://pub.uni-bielefeld.de/record/2519122

Zitieren

Tscherepanow M, Riechers S. An Incremental On-line Classifier for Imbalanced, Incomplete, and Noisy Data. In: Lemaire V, Lamirel J-C, Cuxac P, eds. Proceedings of the ECAI Workshop on Active and Incremental Learning (AIL). 2012: 18-23.
Tscherepanow, M., & Riechers, S. (2012). An Incremental On-line Classifier for Imbalanced, Incomplete, and Noisy Data. In V. Lemaire, J. - C. Lamirel, & P. Cuxac (Eds.), Proceedings of the ECAI Workshop on Active and Incremental Learning (AIL) (pp. 18-23).
Tscherepanow, M., and Riechers, S. (2012). “An Incremental On-line Classifier for Imbalanced, Incomplete, and Noisy Data” in Proceedings of the ECAI Workshop on Active and Incremental Learning (AIL), Lemaire, V., Lamirel, J. - C., and Cuxac, P. eds. 18-23.
Tscherepanow, M., & Riechers, S., 2012. An Incremental On-line Classifier for Imbalanced, Incomplete, and Noisy Data. In V. Lemaire, J. - C. Lamirel, & P. Cuxac, eds. Proceedings of the ECAI Workshop on Active and Incremental Learning (AIL). pp. 18-23.
M. Tscherepanow and S. Riechers, “An Incremental On-line Classifier for Imbalanced, Incomplete, and Noisy Data”, Proceedings of the ECAI Workshop on Active and Incremental Learning (AIL), V. Lemaire, J.-C. Lamirel, and P. Cuxac, eds., 2012, pp.18-23.
Tscherepanow, M., Riechers, S.: An Incremental On-line Classifier for Imbalanced, Incomplete, and Noisy Data. In: Lemaire, V., Lamirel, J.-C., and Cuxac, P. (eds.) Proceedings of the ECAI Workshop on Active and Incremental Learning (AIL). p. 18-23. (2012).
Tscherepanow, Marko, and Riechers, Sören. “An Incremental On-line Classifier for Imbalanced, Incomplete, and Noisy Data”. Proceedings of the ECAI Workshop on Active and Incremental Learning (AIL). Ed. Vincent Lemaire, Jean-Charles Lamirel, and Pascal Cuxac. 2012. 18-23.
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