Feature selection and validation for mass spectral data in proteomics
Feature selection and validation for mass spectral data in proteomics
In the area of proteomics, one of the applications is to detect a given type of disease on the basis of patient blood samples. A well-recognized challenge in classification for this type of problem is that there are thousands of features, but only a limited number of samples available. Thus, feature selection becomes an essential procedure to prevent over-fitting before any classification model can be built. We discuss various ways in selecting the key features from the feature space, with respect to the performance of the classification model, as well as the biological implication
Ni, Jia
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Bennell, Julia
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Thomas, Lyn
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Potts, Chris
58c36fe5-3bcb-4320-a018-509844d4ccff
2006
Ni, Jia
9ccdd9ea-c13e-4945-8b10-a844ea07fce4
Bennell, Julia
38d924bc-c870-4641-9448-1ac8dd663a30
Thomas, Lyn
a3ce3068-328b-4bce-889f-965b0b9d2362
Potts, Chris
58c36fe5-3bcb-4320-a018-509844d4ccff
Ni, Jia, Bennell, Julia, Thomas, Lyn and Potts, Chris
(2006)
Feature selection and validation for mass spectral data in proteomics.
21st European Conference on Operational Research (EURO XXI), Reykjavic, Iceland.
01 - 04 Jul 2006.
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Conference or Workshop Item
(Paper)
Abstract
In the area of proteomics, one of the applications is to detect a given type of disease on the basis of patient blood samples. A well-recognized challenge in classification for this type of problem is that there are thousands of features, but only a limited number of samples available. Thus, feature selection becomes an essential procedure to prevent over-fitting before any classification model can be built. We discuss various ways in selecting the key features from the feature space, with respect to the performance of the classification model, as well as the biological implication
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Published date: 2006
Venue - Dates:
21st European Conference on Operational Research (EURO XXI), Reykjavic, Iceland, 2006-07-01 - 2006-07-04
Identifiers
Local EPrints ID: 56838
URI: http://eprints.soton.ac.uk/id/eprint/56838
PURE UUID: b4dd60a6-c8d8-43d0-a1c2-464531eeb8e7
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Date deposited: 06 Aug 2008
Last modified: 11 Dec 2021 17:50
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Contributors
Author:
Jia Ni
Author:
Julia Bennell
Author:
Lyn Thomas
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