Swarm Optimisation as a New Tool for Data Mining
Authors
Abstract
This paper proposes the use of Particle Swarm Optimisersas a tool for data mining. To evaluate its usefulness, we
empirically compare the performance of three variants of
the Particle Optimiser with another evolutionary
algorithm, namely a Genetic Algorithm, in rule discovery
for classification tasks. Such tasks are considered core
tools for Decision Support Systems in a widespread area,
ranging from the industry, commerce, military and
scientific fields. The data sources used here for
experimental testing are commonly used and considered
as a de facto standard for rule discovery algorithms
reliability ranking. The results obtained in these domains
seem to indicate that Particle Swarm Optimisers are
competitive with other evolutionary techniques, and can be
successfully applied to more demanding problem domains.
Keywords
PSO, Data MiningSubject
Particle Swarm OptimizationConference
IPDPS, April 2003Cited by
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