A hybrid particle swarm/ant colony algorithm for the classification of hierarchical biological data

Holden, Nicholas and Freitas, Alex A. (2005) A hybrid particle swarm/ant colony algorithm for the classification of hierarchical biological data. In: Arabshahi, Payman and Martinoli, Alcherio, eds. Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. IEEE, pp. 100-107. ISBN 0-7803-8916-6. (doi:10.1109/SIS.2005.1501608) (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:14309)

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: http://dx.doi.org/10.1109/SIS.2005.1501608

Abstract

This paper proposes a hybrid PSO/ACO algorithm for hierarchical classification, where the classes to be predicted are arranged in a tree-like hierarchy. The performance of the algorithm is evaluated on a challenging biological data set, involving the hierarchical functional classification of enzymes. The proposed algorithm is compared with an existing PSO for classification, which was also adapted for hierarchical classification.

Item Type:	Book section
DOI/Identification number:	10.1109/SIS.2005.1501608
Uncontrolled keywords:	data mining, classification, bioinformatics, ant colony optimization, particle swarm optimization
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Institutional Unit:	Schools > School of Computing
Former Institutional Unit:	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:	20 May 2025 10:05 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/14309 (The current URI for this page, for reference purposes)

University of Kent Author Information

Freitas, Alex A..

Creator's ORCID:	https://orcid.org/0000-0001-9825-4700
CReDIT Contributor Roles:

Depositors only (login required):

Altmetric

Total Views

Total unique views of this page since July 2020. For more details click on the image.