Skip to main content
Article thumbnail
Location of Repository

A First Study on a Fuzzy Rule-Based Multiclassification System Framework Combining FURIA with Bagging and Feature Selection

By Krzysztof Trawiński, Oscar Cordón and Arnaud Quirin


Abstract — In this work, we conduct a preliminary study considering a fuzzy rule-based multiclassification system design framework based on Fuzzy Unordered Rule Induction Algorithm (FURIA). This advanced method serves as the fuzzy classification rule learning algorithm to derive the component classifiers considering bagging combined with feature selection. We develop a study on the use of both bagging and feature selection to design a final FURIA-based fuzzy multiclassifier applied to ten popular UCI datasets. The results obtained show that this approach provides promising results. I

Year: 2014
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • (external link)
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.