Skip to main content
Kent Academic Repository

Handling continuous attributes in ant colony classification algorithms

Otero, Fernando E.B., Freitas, Alex A., Johnson, Colin G. (2009) Handling continuous attributes in ant colony classification algorithms. In: Proc. of the 2009 IEEE Symposium on Computational Intelligence in Data Mining (CIDM 2009). . pp. 225-231. IEEE ISBN 978-1-4244-2765-9. (doi:10.1109/CIDM.2009.4938653) (KAR id:24089)


Most real-world classification problems involve continuous (real-valued) attributes, as well as, nominal (discrete) attributes. The majority of Ant Colony Optimisation (ACO) classification algorithms have the limitation of only being able to cope with nominal attributes directly. Extending the approach for coping with continuous attributes presented by cAnt-Miner (Ant-Miner coping with continuous attributes), in this paper we propose two new methods for handling continuous attributes in ACO classification algorithms. The first method allows a more flexible representation of continuous attributes' intervals. The second method explores the problem of attribute interaction, which originates from the way that continuous attributes are handled in cAnt-Miner, in order to implement an improved pheromone updating method. Empirical evaluation on eight publicly available data sets shows that the proposed methods facilitate the discovery of more accurate classification models.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/CIDM.2009.4938653
Uncontrolled keywords: ant colony optimization, data mining, classification
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: Fernando Otero
Date Deposited: 29 Mar 2010 12:14 UTC
Last Modified: 16 Nov 2021 10:02 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.