FEATURE DISCRETIZATION AND SELECTION IN MICROARRAY DATA

Artur Ferreira, Mário Figueiredo

Abstract

Tumor and cancer detection from microarray data are important bioinformatics problems. These problems are quite challenging for machine learning methods, since microarray datasets typically have a very large number of features and small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. This paper proposes unsupervised feature discretization and selection methods suited for microarray data. The experimental results reported, conducted on public domain microarray datasets, show that the proposed discretization and selection techniques yield competitive and promising results with the best previous approaches. Moreover, the proposed methods efficiently handle multi-class microarray data.

References

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Paper Citation


in Harvard Style

Ferreira A. and Figueiredo M. (2011). FEATURE DISCRETIZATION AND SELECTION IN MICROARRAY DATA . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011) ISBN 978-989-8425-79-9, pages 457-461. DOI: 10.5220/0003662004650469


in Bibtex Style

@conference{kdir11,
author={Artur Ferreira and Mário Figueiredo},
title={FEATURE DISCRETIZATION AND SELECTION IN MICROARRAY DATA},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)},
year={2011},
pages={457-461},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003662004650469},
isbn={978-989-8425-79-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)
TI - FEATURE DISCRETIZATION AND SELECTION IN MICROARRAY DATA
SN - 978-989-8425-79-9
AU - Ferreira A.
AU - Figueiredo M.
PY - 2011
SP - 457
EP - 461
DO - 10.5220/0003662004650469