Opposite neighborhood: a new method to select reference points of minimal learning machines

Madson Luiz Dantas Dias, Lucas Silva de Sousa, Ajalmar R. da Rocha Neto, Amauri H. Souza Júnior
2018 The European Symposium on Artificial Neural Networks  
This paper introduces a new approach to select reference points in minimal learning machines (MLMs) for classification tasks. The MLM training procedure comprises the selection of a subset of the data, named reference points (RPs), that is used to build a linear regression model between distances taken in the input and output spaces. In this matter, we propose a strategy, named opposite neighborhood (ON), to tackle the problem of selecting RPs by locating RPs out of class-overlapping regions.
more » ... periments were carried out using UCI data sets. As a result, the proposal is able to both produce sparser models and achieve competitive performance when compared to the regular MLM.
dblp:conf/esann/DiasSNJ18 fatcat:n4y34cagazfofelhduxxpxabxi