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Feature selection techniques and applications in bioinformatics

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Date Issued:
2011
Summary:
Possibly the largest problem when working in bioinformatics is the large amount of data to sift through to find useful information. This thesis shows that the use of feature selection (a method of removing irrelevant and redundant information from the dataset) is a useful and even necessary technique to use in these large datasets. This thesis also presents a new method in comparing classes to each other through the use of their features. It also provides a thorough analysis of the use of various feature selection techniques and classifier in different scenarios from bioinformatics. Overall, this thesis shows the importance of the use of feature selection in bioinformatics.
Title: Feature selection techniques and applications in bioinformatics.
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Name(s): Dittman, David
College of Engineering and Computer Science
Department of Computer and Electrical Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Issued: 2011
Publisher: Florida Atlantic University
Physical Form: electronic
Extent: xiii, 132 p. : ill.
Language(s): English
Summary: Possibly the largest problem when working in bioinformatics is the large amount of data to sift through to find useful information. This thesis shows that the use of feature selection (a method of removing irrelevant and redundant information from the dataset) is a useful and even necessary technique to use in these large datasets. This thesis also presents a new method in comparing classes to each other through the use of their features. It also provides a thorough analysis of the use of various feature selection techniques and classifier in different scenarios from bioinformatics. Overall, this thesis shows the importance of the use of feature selection in bioinformatics.
Identifier: 749897270 (oclc), 3175016 (digitool), FADT3175016 (IID), fau:3697 (fedora)
Note(s): by David Dittman.
Thesis (M.S.C.S.)--Florida Atlantic University, 2011.
Includes bibliography.
Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.
Subject(s): Bioinformatifcs
Data mining -- Technological innovations
Computational biology
Combinatorial group theory
Filters (Mathematics)
Ranking and selection (Statistics)
Held by: FBoU FAUER
Persistent Link to This Record: http://purl.flvc.org/FAU/3175016
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU