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ESANN
2008
14 years 11 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 ...
Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Ales...
ICMLA
2008
14 years 11 months ago
Predicting Algorithm Accuracy with a Small Set of Effective Meta-Features
We revisit 26 meta-features typically used in the context of meta-learning for model selection. Using visual analysis and computational complexity considerations, we find 4 meta-f...
Jun Won Lee, Christophe G. Giraud-Carrier
JMLR
2010
139views more  JMLR 2010»
14 years 4 months ago
On the Foundations of Noise-free Selective Classification
We consider selective classification, a term we adopt here to refer to `classification with a reject option.' The essence in selective classification is to trade-off classifi...
Ran El-Yaniv, Yair Wiener
BMCBI
2006
142views more  BMCBI 2006»
14 years 9 months ago
Improving the Performance of SVM-RFE to Select Genes in Microarray Data
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
Yuanyuan Ding, Dawn Wilkins
BMCBI
2006
101views more  BMCBI 2006»
14 years 9 months ago
SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms
Background: The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validatio...
Tim Van den Bulcke, Koen Van Leemput, Bart Naudts,...