A new approach to three ensemble neural network rule extraction using recursive-rule extraction algorithm
Yoichi Hayashi, Ryusuke Sato, Sushmita Mitra · 2013
In this paper, we propose a Three Ensemble neural network rule extraction algorithm. Then we investigate Hayashi's first question, “Can the Ensemble-Recursive-Rule eXtraction (E-Re-RX) algorithm be extended to an ensemble neural network consisting of three or more MLPs and extract comprehensible rules?” The E-Re-RX algorithm is an effective rule extraction algorithm for dealing with data sets that mix discrete and continuous attributes. Using the experimental results, we consider the three MLP ensemble Re-RX algorithm from various points of view. Finally, we present provisional positive conclusions.