- author = "I. {De Falco} and E. Tarantino and A. {Della Cioppa} and F. Fontanella",
- title = "An Innovative Approach to Genetic Programming-based Clustering",
- booktitle = "9th Online World Conference on Soft Computing in Industrial Applications",
- year = "2004",
- editor = "Ajith Abraham and Bernard {de Baets} and Mario Koeppen and Bertram Nickolay",
- volume = "34",
- series = "Advances in Soft Computing",
- pages = "55--64",
- address = "On the World Wide Web",
- month = "20 " # sep # " - 8 " # oct,
- organisation = "World Federation on Soft Computing (WFSC)",
- publisher = "Springer-Verlag",
- keywords = "genetic algorithms, genetic programming, clustering",
- isbn13 = "978-3-540-31649-7",
-
URL = "
http://webuser.unicas.it/fontanella/papers/WSC04.pdf",
-
DOI = "
doi:10.1007/3-540-31662-0_4",
- size = "10 pages",
- abstract = "Most of the classical clustering algorithms are strongly dependent on, and sensitive to, parameters such as number of expected clusters and resolution level. To overcome this drawback, in this paper a Genetic Programming framework, capable of performing an automatic data clustering is presented. Moreover, a novel way of representing clusters which provides intelligible information on patterns is introduced together with an innovative clustering process. The effectiveness of the implemented partitioning system is estimated on a medical domain by means of evaluation indices",
-
notes = "WSC9
Clusters represented using GP evolved functions. Grammar. Fitness is linear combination of cluster homogeneity and separation. Non standard crossover. Multiple classes. UCI dermatological benchmark.",
