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ESANN
2008

A method for robust variable selection with significance assessment

13 years 4 months ago
A method for robust variable selection with significance assessment
Our goal is proposing an unbiased framework for gene expression analysis based on variable selection combined with a significance assessment step. We start by discussing the need of such a framework by illustrating the dramatic effect of a biased approach especially when the sample size is small. Then we describe our analysis protocol, based on two main ingredients. The first is a gene selection core based on elastic net regularization where we explicitly take into account regularization parameter tuning. The second is a general architecture to assess the statistical significance of the model via cross validation and permutation testing. Finally we challenge the system on real data experiments, and study its performance when changing variable selection algorithm or the dataset size. 1 Motivation The ultimate goal of cancer research is the design of effective targeted therapies, which can be achieved only through accurate disease classification and molecular mechanisms understanding. A...
Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Ales
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where ESANN
Authors Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Alessandro Verri
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