Incorporating Dynamic Uncertainties into a Fuzzy Classifier
Jens Hülsmann, Andreas Buschermohle, Werner Brockmann
Available Online August 2011.
- https://doi.org/10.2991/eusflat.2011.4How to use a DOI?
- fuzzy classifier, uncertainty, trust management
- Dealing with classification problems in practice often has to cope with uncertain information, either in the training or in the operation phase or both. Modeling these uncertainties allows to enhance the robustness or performance of the classifier. In this paper we focus on the operation phase and present a general, but simple extension to rule based fuzzy classifier to do so. Therefor uncertain features are gradually and dimension wise faded out of the classification process. An artificial twodimensional dataset is used to visualize the effectiveness of this approach. Investigations on three benchmark datasets shows the performance and gain in robustness.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jens Hülsmann AU - Andreas Buschermohle AU - Werner Brockmann PY - 2011/08 DA - 2011/08 TI - Incorporating Dynamic Uncertainties into a Fuzzy Classifier BT - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 388 EP - 395 SN - 1951-6851 UR - https://doi.org/10.2991/eusflat.2011.4 DO - https://doi.org/10.2991/eusflat.2011.4 ID - Hülsmann2011/08 ER -