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Class Segmentation to Improve Fuzzy Prototype Construction: Visualization and Characterization of Non Homogeneous Classes
2006 IEEE International Conference on Fuzzy Systems
In this paper, we present a new method to construct fuzzy prototypes of heterogeneous classes, in a supervised learning context. Heterogeneous classes are classes where the coexistence of far behaviours can be observed. Our approach consists in two stages. The first one enables to discover, in an original method, the different behaviours within a class by decomposing it in subclasses. In the second stage, we construct a fuzzy prototype for each subclass by using typicality degrees. Thanks todoi:10.1109/fuzzy.2006.1681766 dblp:conf/fuzzIEEE/ForestRB06 fatcat:a6k7b4eccrdsjnrqfi23flvkiu