A Pseudoregression Formulation of Emphasized Soft Target Procedures for Classification Problems

Abstract. Replacing a hard decision by a soft targets version including an attentional mechanism provides performance advantage and flexibility to solve classification tasks. In this paper, we modify the standard emphasized soft target method by proposing two new ideas, to avoid unnecessary updating and inappropriate definition of soft targets, in order to increase designs performance. Experimental results using MLPs show the effectiveness of this approach compared with the standard ST and other methods.