Fertig, Cristina S. and Freitas, Alex A. and Arruda, Lucia V. R. and Kaestner, Celso A.A. (1999) A Fuzzy Beam-Search Rule Induction Algorithm. In: Zytkow, Jan M. and Rauch, Jan, eds. Principles of Data Mining and Knowledge Discovery. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 341-347. ISBN 978-3-540-66490-1. E-ISBN 978-3-540-48247-5. (doi:10.1007/978-3-540-48247-5_40) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:21711)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: https://doi.org/10.1007/978-3-540-48247-5_40 |
Abstract
This paper proposes a fuzzy beam search rule induction algorithm for the classification task. The use of fuzzy logic and fuzzy sets not only provides us with a powerful, flexible approach to cope with uncertainty, but also allows us to express the discovered rules in a representation more intuitive and comprehensible for the user, by using linguistic terms (such as low, medium, high) rather than continuous, numeric values in rule conditions. The proposed algorithm is evaluated in two public domain data sets.
Item Type: | Book section |
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DOI/Identification number: | 10.1007/978-3-540-48247-5_40 |
Uncontrolled keywords: | Class Diagram; State Diagram; Object Constraint Language; State Schedule; Textual Language |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Mark Wheadon |
Date Deposited: | 02 Sep 2009 11:39 UTC |
Last Modified: | 05 Nov 2024 10:00 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/21711 (The current URI for this page, for reference purposes) |
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