Designing nearest neighbour classifiers by the evolution of a population of prototypes.
Fernando Fernández, Pedro Isasi · 2001
A new evolutionary algorithm to design nearest neightbour classifiers is presented in this paper. Main design topics of this sort of classifiers are the number of prototypes used and their position. This algorithm is based on the evolution of a population of prototypes that try to achieve an equilibrium by nding the right size of the population and the position of each prototype in the environment, solving at the same time both design topics above. A biological point of view is given to explain most of the concepts introduced, as well as the operators used in evolution.