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Combining one class fuzzy KNN’s

  • Autori: DI GESU', V.; LO BOSCO, G.
  • Anno di pubblicazione: 2007
  • Tipologia: Contributo in atti di convegno pubblicato in volume
  • OA Link:


This paper introduces a parallel combination of N > 2 one class fuzzy KNN (FKNN) classifiers. The classifier combination consists of a new optimization procedure based on a genetic algorithm applied to FKNN’s, that differ in the kind of similarity used. We tested the integration techniques in the case of N = 5 similarities that have been recently introduced to face with categorical data sets. The assessment of the method has been carried out on two public data set, the Masquerading User Data ( and the badges database on the UCI Machine Learning Repository ( Preliminary results show the better performance obtained by the fuzzy integration respect to the crisp one.