Incorporating ranking rules into k nearest neighbours
Noelia Rico, Raúl Pérez‐Fernández, Irene Dı́az · 2019
This paper describes how distance-based classification methods could be improved by incorporating ranking rules, which are old acquaintances of aggregation and social choice theorists. Specifically, a novel method incorporating two prominent ranking rules (namely, the plurality and the Borda count ranking rules) into the distance-based classification method of nearest neighbours is presented. Some exploratory experiments have been conducted, obtaining encouraging results. Interestingly, the newly proposed method seems to turn the classic method of nearest neighbours independent of the chosen distance metric while not compromising its performance significantly.