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Mining comprehensible rules from data with an ant colony algorithm

Parpinelli, Rafael S. and Lopes, Heitor S. and Freitas, Alex A. (2003) Mining comprehensible rules from data with an ant colony algorithm. In: Bittencourt, Guilherme and Ramalho, Geber L., eds. Advances in Artificial Intelligence 16th Brazilian Symposium on Artificial Intelligence. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 259-269. ISBN 978-3-540-00124-9. E-ISBN 978-3-540-36127-5. (doi:10.1007/3-540-36127-8_25) (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:13704)

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)
Official URL
http://dx.doi.org/10.1007/3-540-36127-8_25

Abstract

This work describes an algorithm for data mining called Ant-Miner (Ant Colony-based Data Miner).The goal of Ant-Miner is to extract classification rules from data. The algorithm is inspired by both research on the behavior of real ant colonies and some data mining concepts and principles. We compare the performance of Ant-Miner with CN2, a well-known data mining algorithm for classification, in six public domain data sets. The results provide evidence that: (a) Ant-Miner is competitive with CN2 with respect to predictive accuracy; and (b) The rule lists discovered by Ant-Miner are considerably simpler (smaller) than those discovered by CN2.

Item Type: Book section
DOI/Identification number: 10.1007/3-540-36127-8_25
Uncontrolled keywords: data mining, machine learning, ant colony algorithms
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 17:59 UTC
Last Modified: 16 Feb 2021 12:24 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/13704 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
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