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Paper details
Number 2 - June 2016
Volume 26 - 2016
An n-ary λ-averaging based similarity classifier
Onesfole Kurama, Pasi Luukka, Mikael Collan
Abstract
We introduce a new n-ary λ similarity classifier that is based on a new n-ary λ-averaging operator in the aggregation of similarities. This work is a natural extension of earlier research on similarity based classification in which aggregation is commonly performed by using the OWA-operator. So far λ -averaging has been used only in binary aggregation. Here the λ-averaging operator is extended to the n-ary aggregation case by using t-norms and t-conorms. We examine four different n-ary norms and test the new similarity classifier with five medical data sets. The new method seems to perform well when compared with the similarity classifier.
Keywords
similarity classifier with λ-averaging, n-ary λ-averaging operator, n-ary t-norm, n-ary t-conorm, classification