A particle swarm data miner

26Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper describes the implementation of Data Mining tasks using Particle Swarm Optimisers. The object of our research has been to apply such algorithms to classification rule discovery. Results, concerning accuracy and speed performance, were empirically compared with another evolutionary algorithm, namely a Genetic Algorithm and with J48 - a Java implementation of C4.5. The data sets used for experimental testing have already been widely used and proven reliable for testing other Data Mining algorithms. The obtained results seem to indicate that Particle Swarm Optimisers are competitive with other evolutionary techniques, and could come to be successfully applied to more demanding problem domains. © Springer-Verlag Berlin Heidelberg 2003.

Cite

CITATION STYLE

APA

Sousa, T., Silva, A., & Neves, A. (2003). A particle swarm data miner. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2902, 43–53. https://doi.org/10.1007/978-3-540-24580-3_12

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free