Applying Fuzzy CoCo to breast cancer diagnosis

Carlos Andres Pena-Reyes, Moshe Sipper

Research output: Contribution to conferencePaperpeer-review

16 Scopus citations

Abstract

Coevolutionary algorithms have received increased attention in the past few years within the domain of evolutionary computation. In this paper, we combine the search power of coevolutionary computation with the expressive power of fuzzy systems, introducing a novel algorithm, Fuzzy CoCo: Fuzzy Cooperative Coevolution. We demonstrate the efficacy of Fuzzy CoCo by applying it to a hard, real-world problem - breast cancer diagnosis - obtaining the best results to date while expending less computational effort than formerly.

Original languageEnglish
Pages1168-1175
Number of pages8
StatePublished - 3 Dec 2000
Externally publishedYes
EventProceedings of the 2000 Congress on Evolutionary Computation - California, CA, USA
Duration: 16 Jul 200019 Jul 2000

Conference

ConferenceProceedings of the 2000 Congress on Evolutionary Computation
CityCalifornia, CA, USA
Period16/07/0019/07/00

Fingerprint

Dive into the research topics of 'Applying Fuzzy CoCo to breast cancer diagnosis'. Together they form a unique fingerprint.

Cite this