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2016

Evolutionary fuzzy k-nearest neighbors algorithm using interval-valued fuzzy sets

4 years 3 months ago
Evolutionary fuzzy k-nearest neighbors algorithm using interval-valued fuzzy sets
One of the most known and effective methods in supervised classification is the K-Nearest Neighbors classifier. Several approaches have been proposed to enhance its precision, with the Fuzzy K-Nearest Neighbors (Fuzzy-kNN) classifier being among the most successful ones. However, despite its good behavior, Fuzzy-kNN lacks of a method for properly defining several mechanisms regarding the representation of the relationship between the instances and the classes of the classification problems. Such a method would be very desirable, since it would potentially lead to an improvement in the precision of the classifier. In this work we present a new approach, Evolutionary Fuzzy K-Nearest Neighbors classifier using Interval-Valued Fuzzy Sets (EF-kNN-IVFS), incorporating interval-valued fuzzy sets for computing the memberships of training instances in Fuzzy-kNN. It is based on the representation of multiple choices of two key parameters of Fuzzy-kNN: One is applied in the definition o...
Joaquín Derrac, Francisco Chiclana, Salvado
Added 05 Apr 2016
Updated 05 Apr 2016
Type Journal
Year 2016
Where ISCI
Authors Joaquín Derrac, Francisco Chiclana, Salvador García, Francisco Herrera
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