FuzzyRULES-II: A new approach to fuzzy rule induction from numerical data

Afifi, Ashraf

Abstract

© 2016 The authors and IOS Press. All rights reserved. Data mining is a broad area that integrates research efforts from several fields with the aim of processing large volumes of data into knowledge bases for better decision making. Since numerical and nominal data are equally important in practical data mining applications, dealing with different types of data items are among the most important problems in data mining research and development. This paper introduces a new fuzzy rule induction algorithm, able to deal properly with either numerical or nominal attributes, for the creation of classification and predictive models. To better handle numerical data, fuzzy sets are used to represent intervals in the domains of numerical attributes. Experimental results have shown that the proposed algorithm produces robust and general models that can be used for prediction as well as for classification.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Fuzzy Systems and Data Mining
• Acceptance Date: Aug 1, 2015
• Publication Date: Jan 1, 2016
• Deposit Date: Feb 2, 2017
• Publicly Available Date: Feb 17, 2017
• Journal: Frontiers in Artificial Intelligence and Applications
• Print ISSN: 0922-6389
• Publisher: IOS Press
• Peer Reviewed: Peer Reviewed
• Volume: 281
• Pages: 91-100
• Book Title: Fuzzy System and Data Mining
• ISBN: 9781614996187
• DOI: https://doi.org/10.3233/978-1-61499-619-4-91
• Keywords: data mining, rule induction, numerical output prediction, discretisation, fuzzy sets
• Public URL: https://uwe-repository.worktribe.com/output/916147
• Publisher URL: http://dx.doi.org/10.3233/978-1-61499-619-4-91
• Additional Information: Additional Information : This is the author's accepted manuscript: Fuzzy System and Data Mining, Vol 281, Afifi, A., FuzzyRULES-II: A new approach to fuzzy rule induction from numerical data, 91-100, Copyright 2016, with permission from IOS Press. The publication is available at IOS Press through http://dx.doi.org/10.3233/978-1-61499-619-4-91.; Title of Conference or Conference Proceedings : Proceedings of the 2015 International Conference on Fuzzy Systems and Data Mining (FSDM-2015), Shanghai, China
• Contract Date: Feb 2, 2017