An ensemble approach for phenotype classification based on fuzzy partitioning of gene expression data

A. Dragomir, I. Maraziotis, A. Bezerianos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We focus on developing a pattern recognition method suitable for performing supervised analysis tasks on molecular data resulting from microarray experiments. Molecular characterization of tissue samples using microarray gene expression profiling is expected to uncover fundamental aspects related to cancer diagnosis and drug discovery. There is therefore a need for reliable, accurate classification methods. With this study we propose a framework for constructing an ensemble of individually trained SVM classifiers, each of them specialized on subsets of the input space. The fuzzy approach used for partitioning the data produces overlapping subsets of the input space that facilitates subsequent classification tasks.

Original languageEnglish (US)
Title of host publication28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Pages5834-5837
Number of pages4
DOIs
StatePublished - Dec 1 2006
Event28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States
Duration: Aug 30 2006Sep 3 2006

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN (Print)0589-1019

Other

Other28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
CountryUnited States
CityNew York, NY
Period8/30/069/3/06

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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    Dragomir, A., Maraziotis, I., & Bezerianos, A. (2006). An ensemble approach for phenotype classification based on fuzzy partitioning of gene expression data. In 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 (pp. 5834-5837). [4029429] (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings). https://doi.org/10.1109/IEMBS.2006.259348