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13.706 Articles in journals published by the UPC
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  • 2004, Vol. XI, Núm. 2-3
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A cost-sensitive learning algorithm for fuzzy rule-based classifiers

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Beck, Sebastian
Mikut, Ralf
Jäkel, Jens
Document typeArticle
Defense date2004
PublisherUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
Designing classifiers may follow different goals. Which goal to prefer among others depends on the given cost situation and the class distribution. For example, a classifier designed for best accuracy in terms of misclassifica- tions may fail when the cost of misclassification of one class is much higher than that of the other. This paper presents a decision-theoretic extension to make fuzzy rule generation cost-sensitive. Furthermore, it will be shown how interpretability aspects and the costs of feature acquisition can be ac- counted for during classifier design. Natural language text is used to explain the generated fuzzy rules and their design process
URIhttp://hdl.handle.net/2099/3645
ISSN1134-5632
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