A new approach to three ensemble neural network rule extraction using recursive-rule extraction algorithm

Yoichi Hayashi, Ryusuke Sato, Sushmita Mitra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2013 International Joint Conference on Neural Networks, IJCNN 2013
DOIs
Publication statusPublished - 1 Dec 2013
Event2013 International Joint Conference on Neural Networks, IJCNN 2013 - Dallas, TX, United States
Duration: 4 Aug 20139 Aug 2013

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Conference

Conference2013 International Joint Conference on Neural Networks, IJCNN 2013
CountryUnited States
CityDallas, TX
Period4/08/139/08/13

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Cite this

Hayashi, Y., Sato, R., & Mitra, S. (2013). A new approach to three ensemble neural network rule extraction using recursive-rule extraction algorithm. In 2013 International Joint Conference on Neural Networks, IJCNN 2013 [6706823] (Proceedings of the International Joint Conference on Neural Networks). https://doi.org/10.1109/IJCNN.2013.6706823