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Applied Computational Intelligence and Soft Computing
Volume 2018, Article ID 4084850, 20 pages
https://doi.org/10.1155/2018/4084850
Research Article

A Comparison Study on Rule Extraction from Neural Network Ensembles, Boosted Shallow Trees, and SVMs

1Department of Computer Science, University of Applied Sciences and Arts Western Switzerland, Rue de la Prairie 4, 1202 Geneva, Switzerland
2Department of Computer Science, University of Geneva, Route de Drize 7, 1227 Carouge, Switzerland
3Department of Computer Science, Meiji University, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan

Correspondence should be addressed to Guido Bologna; hc.egseh@angolob.odiug

Received 27 July 2017; Revised 17 November 2017; Accepted 4 December 2017; Published 9 January 2018

Academic Editor: Erich Peter Klement

Copyright © 2018 Guido Bologna and Yoichi Hayashi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [2 citations]

The following is the list of published articles that have cited the current article.

  • Yoichi Hayashi, and Tatsuhiro Oishi, “High Accuracy-priority Rule Extraction for Reconciling Accuracy and Interpretability in Credit Scoring,” New Generation Computing, 2018. View at Publisher · View at Google Scholar
  • Naziha Sendi, Nadia Abchiche-Mimouni, and Farida Zehraoui, “Towards a Transparent Deep Ensemble Method Based on Multiagent Argumentation,” Explainable, Transparent Autonomous Agents and Multi-Agent Systems, vol. 11763, pp. 3–21, 2019. View at Publisher · View at Google Scholar