Fuzzy Rough Positive Region based Nearest Neighbour Classification

Nele Verbiest, Chris Cornelis, Richard Jensen

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (Nid-Cyfnodolyn fathau)

19 Dyfyniadau(SciVal)
127 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

This paper proposes a classifier that uses fuzzy rough set theory to improve the Fuzzy Nearest Neighbour (FNN) classifier. We show that previous attempts to use fuzzy rough set theory to improve the FNN algorithm have some shortcomings and we overcome them by using the fuzzy positive region to measure the quality of the nearest neighbours in the FNN classifier. A preliminary experimental evaluation shows that the new approach generally improves upon existing methods.

Iaith wreiddiolSaesneg
Teitl2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Man cyhoeddiNEW YORK
CyhoeddwrIEEE Press
Tudalennau1961-1967
Nifer y tudalennau7
ISBN (Argraffiad)978-1-4673-1506-7
StatwsCyhoeddwyd - 2012
DigwyddiadIEEE International Conference on Fuzzy Systems (FUZZ-IEEE)/International Joint Conference on Neural Networks (IJCNN)/IEEE Congress on Evolutionary Computation (IEEE-CEC)/IEEE World Congress on Computational Intelligence (IEEE-WCCI) - Brisbane
Hyd: 10 Meh 201215 Meh 2012

Cynhadledd

CynhadleddIEEE International Conference on Fuzzy Systems (FUZZ-IEEE)/International Joint Conference on Neural Networks (IJCNN)/IEEE Congress on Evolutionary Computation (IEEE-CEC)/IEEE World Congress on Computational Intelligence (IEEE-WCCI)
DinasBrisbane
Cyfnod10 Meh 201215 Meh 2012

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