WIT Press

Rule Extraction From Neural Networks In Data Mining Applications

Price

Free (open access)

Paper DOI

10.2495/DATA980211

Volume

22

Pages

13

Published

1998

Size

1,010 kb

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