TY - JOUR
T1 - Fuzzy-Rough Nearest Neighbour Classification
AU - Jensen, Richard
AU - Cornelis, Chris
PY - 2011/12/31
Y1 - 2011/12/31
N2 - A new fuzzy-rough nearest neighbour (FRNN) classification algorithm is presented in this paper, as an alternative to Sarkar’s fuzzy-rough ownership function (FRNN-O) approach. By contrast to the latter, our method uses the nearest neighbours to construct lower and upper approximations of decision classes, and classifies test instances based on their membership to these approximations. In the experimental analysis, we evaluate our approach with both classical fuzzy-rough approximations (based on an implicator and a t-norm), as well as with the recently introduced vaguely quantified rough sets. Preliminary results are very good, and in general FRNN outperforms FRNN-O, as well as the traditional fuzzy nearest neighbour (FNN) algorithm.
AB - A new fuzzy-rough nearest neighbour (FRNN) classification algorithm is presented in this paper, as an alternative to Sarkar’s fuzzy-rough ownership function (FRNN-O) approach. By contrast to the latter, our method uses the nearest neighbours to construct lower and upper approximations of decision classes, and classifies test instances based on their membership to these approximations. In the experimental analysis, we evaluate our approach with both classical fuzzy-rough approximations (based on an implicator and a t-norm), as well as with the recently introduced vaguely quantified rough sets. Preliminary results are very good, and in general FRNN outperforms FRNN-O, as well as the traditional fuzzy nearest neighbour (FNN) algorithm.
UR - http://hdl.handle.net/2160/8742
U2 - 10.1007/978-3-642-18302-7_4
DO - 10.1007/978-3-642-18302-7_4
M3 - Article
SN - 1861-2067
VL - XIII
SP - 56
EP - 72
JO - Transactions on Rough Sets
JF - Transactions on Rough Sets
ER -