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Output details

11 - Computer Science and Informatics

University of Kent

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Output 29 of 117 in the submission

Output title

cAnt-Miner: An Ant Colony Classification Algorithm to Cope with Continuous Attributes

Type

E - Conference contribution

DOI

10.1007/978-3-540-87527-7_5

Name of conference/published proceedings

Ant Colony Optimization and Swarm Intelligence (Proc. ANTS 2008), LNCS 5217

Volume number

5217

Issue number

First page of article

ISSN of proceedings

1611-3349

Year of publication

2008

URL

Number of additional authors

Additional information

<24> This paper proposes the first version of the Ant-Miner classification algorithm capable of dealing with continuous attributes. Many variations of the Ant-Miner algorithm (2002) have been proposed since the original highly influential paper, but until this publication all of those had the limitation of coping only with categorical (not continuous) attributes. After six years, this paper enabled ant colony classification algorithms to be used in new domains: e.g. gene expression data analysis and stock market trend prediction. The paper was published in the main international conference on Swarm Intelligence (acceptance rate of full papers: 18%).

Interdisciplinary

Cross-referral requested

Research group

I - Computational Intelligence Group

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract