Author(s)

Eduardo R. Hruschka

Abstract

This work deals with the efficient discovery of valuable and nonobvious information from large collections of data, using Computacional Intelligence tools. For this purpose, a . study about knowledge acquirement from supervised neural networks employed for classification problems is presented. An algorithm for rule extraction from neural networks, based on the work by Lu et al. [1] in 1996, is developed. This algorithm, named Modified RX, is experimentally evaluated in three different domains. The results are compared to those obtained by classification trees. In respect of the efficacy , one observes that the s

Keywords