A novel grammar-based genetic programming approach to clustering

Authors:
I. De Falco;E. Tarantino;A. Delia Cioppa;F. Fontanella
Affiliations:
ICAR - CNR, Naples, Italy;ICAR - CNR, Naples, Italy;University of Salerno, Fisciano (SA), Italy;DIS University of Naples, Via Claudio, 21, 80125 Naples, ITALY
Venue:
Proceedings of the 2005 ACM symposium on Applied computing
Year:
2005

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Abstract

Most of the classical methods for clustering analysis require the user setting of number of clusters. To surmount this problem, in this paper a grammar-based Genetic Programming approach to automatic data clustering is presented. An innovative clustering process is conceived strictly linked to a novel cluster representation which provides intelligible information on patterns. The efficacy of the implemented partitioning system is estimated on a medical domain by exploiting expressly defined evaluation indices. Furthermore, a comparison with other clustering tools is performed.