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Pattern-based feature selection in genomics and proteomics

delete2006-10-18
delete25
PRE
AI
G
Gabriela Alexe
S
Sorin Alexe
P
Peter L. Hammer *
B
Béla Vízvári
DOI：10.1007/s10479-006-0084-xdelete
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Abstract

Abstract

En 中文
A major difficulty in bioinformatics is due to the size of the datasets, which contain frequently large numbers of variables. In this study, we present a two-step procedure for feature selection. In a first filtering stage, a relatively small subset of features is identified on the basis of several criteria. In the second stage, the importance of the selected variables is evaluated based on the frequency of their participation in relevant patterns and low impact variables are eliminated. This step is applied iteratively, until arriving to a Pareto-optimal support set, which balances the conflicting criteria of simplicity and accuracy.
Keywords:
feature selection
genomics
proteomics
logical analysis of data
LAD
patterns

Journal

Annals of Operations Research cover
Annals of Operations Research
IF:
4.5
Papers:
8.0K
Citations:
2.1W

Organization

No organization information available