A New Approach to Fuzzy-Rough Nearest Neighbour Classification [chapter]

Richard Jensen, Chris Cornelis
2008 Lecture Notes in Computer Science  
In this paper, we present a new fuzzy-rough nearest neighbour (FRNN) classification algorithm, as an alternative to Sarkar's fuzzyrough 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
more » ... 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 both FRNN-O, as well as the traditional fuzzy nearest neighbour (FNN) algorithm.
doi:10.1007/978-3-540-88425-5_32 fatcat:7qiiqibtonbyzefzuoqhpc7cf4