NDLI: Feature set enhancement via hierarchical clustering for microarray classification

Content Provider	IEEE Xplore Digital Library
Author	Bosio, M. Pujalte, P.B. Salembier, P. Oliveras-Verges, A.
Copyright Year	2011
Description	Author affiliation: Department of Signal Theory and Communications, Technical University of Catalonia, UPC-Campus Nord, C/ Jordi Girona, 1-3, 08034, Barcelona, Spain (Bosio, M.; Pujalte, P.B.; Salembier, P.; Oliveras-Verges, A.)
Abstract	A new method for gene expression classification is proposed in this paper. In a first step, the original feature set is enriched by including new features, called metagenes, produced via hierarchical clustering. In a second step, a reliable classifier is built from a wrapper feature selection process. The selection relies on two criteria: the classical classification error rate and a new reliability measure. As a result, a classifier with good predictive ability using as few features as possible to reduce the risk of overfitting is obtained. This method has been tested on three public cancer datasets: leukemia, lymphoma and colon. The proposed method has obtained interesting classification results and the experiments have confirmed the utility of both metagenes and feature ranking criterion to improve the final classifier.
Starting Page	226
Ending Page	229
File Size	260545
Page Count	4
File Format	PDF
ISBN	9781467304917
ISSN	21503001
e-ISBN	9781467304900
e-ISBN	9781467304894
DOI	10.1109/GENSiPS.2011.6169486
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	cancer microarray classification Error analysis Clustering algorithms hierarchical clustering Colon Reliability Gene expression feature selection Cancer Principal component analysis Treelet
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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