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Improving the interpretability of classification rules in sparse bioinformatics datasets

Smaldon, James, Freitas, Alex A. (2006) Improving the interpretability of classification rules in sparse bioinformatics datasets. In: Bramer, Max and Coenen, Frans and Tuson, Andrew, eds. Research and Development in Intelligent Systems XXIII - Proc. AI-2006. Research and Development Series (23). pp. 377-381. Springer-Verlag, New York ISBN 1-84628-662-X. (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:14384)

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. (Contact us about this Publication)
Item Type: Conference or workshop item (Paper)
Additional information: Proceedings of AI-2006, the Twenty-Sixth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
Uncontrolled keywords: data mining, classification, bioinformatics, ant colony optimization
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: 24 Nov 2008 18:03 UTC
Last Modified: 16 Feb 2021 12:25 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/14384 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
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