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EUSFLAT
2003

Fuzzy models for prediction based on random set semantics

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Fuzzy models for prediction based on random set semantics
In this paper we propose a random set framework for learning linguistic models for prediction problems. We show how we can model prediction problems based on learning linguistic prototypes defined using joint mass assignments on sets of labels. The potential of this approach is then demonstrated by its application to a model and by benchmark problem and comparing the results obtained with those from other state-of-the-art learning algorithms.
Nicholas J. Randon, Jonathan Lawry
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where EUSFLAT
Authors Nicholas J. Randon, Jonathan Lawry
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