International Journal of Applied Mathematics and Computer Science (Jun 2016)

An ɴ-ary λ-averaging based similarity classifier

  • Kurama Onesfole,
  • Luukka Pasi,
  • Collan Mikael

Journal volume & issue
Vol. 26, no. 2
pp. 407 – 421


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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.