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In this article, the problem of function approximation is studied using the paradigm of the nearest prototypes. A method is proposed to construct prototypes using similarity relations; the relations are constructed using the measurement quality of similarity and the metaheuristic UMDA. For every class of similarity, a prototype is constructed. The experimental results show that the proposed method achieves a significant reduction of the quantity of instances to consider, while significant differences do not exist with regard to the performance reached with all the instances.