Improving the genetic algorithm of SLAVE
Antonio González, Raúl Pérez · 2009
The genetic iterative approach has shown to be useful for developing fuzzy rule learning algorithms. The goal of this paper 1 is to extend the iterative scheme of SLAVE for obtaining a complete rule in each iteration, reducing the needed time for the learning process. Thus, we analize this extension and we present a wide experimental study for showing the behaviour of the new algorithm.