title: |
Incorporating Dynamic Uncertainties into a Fuzzy Classifier |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
| pages: | 388 - 395 | |
DOI: |
To be assigned soon (how to use a DOI) | |
author(s): |
Jens H¨¹lsmann, Andreas Buschermohle, Werner Brockmann |
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publication date: |
July 2011 |
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keywords: |
fuzzy classifier, uncertainty, trust management |
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abstract: |
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. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |