Subgroup Discovery trhough Evolutionary Fuzzy Systems applied to Bioinformatic problems

Date

2011-03-01

Advisors

Journal Title

Journal ISSN

ISSN

DOI

Volume Title

Publisher

Technical Report DMU

Type

Other

Peer reviewed

No

Abstract

Subgroup discovery is a descriptive data mining technique using supervised learning. This paper presents a summary about the main properties and elements about subgroup discovery task. In addition, we will focus on the suitability and potential of the search performed by evolutionary algorithms in order to apply in the development of subgroup discovery algorithms, and in the use of fuzzy logic which is a soft computing technique very close to the human reasoning. The hybridisation of both techniques are well known as evolutionary fuzzy system. The most relevant applications of evolutionary fuzzy systems for subgroup discovery in the bioinformatics domains are outlined in this work. Specifically, these algorithms are applied to a problem based on the Influenza A virus and the accute sore throat problem.

Description

Keywords

Data Mining, Fuzzy systems, evolutionary computing

Citation

Elizondo, D. and Carmona, C.J. (2011) Subgroup Discovery trhough Evolutionary Fuzzy Systems applied to Bioinformatic problems.

Rights

Research Institute