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ESANN
2008
13 years 7 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...
CIKM
2010
Springer
13 years 3 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan
BMCBI
2006
82views more  BMCBI 2006»
13 years 6 months ago
Profiling alternatively spliced mRNA isoforms for prostate cancer classification
Background: Prostate cancer is one of the leading causes of cancer illness and death among men in the United States and world wide. There is an urgent need to discover good biomar...
Chaolin Zhang, Hai-Ri Li, Jian-Bing Fan, Jessica W...
BMCBI
2002
195views more  BMCBI 2002»
13 years 6 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
KDD
2010
ACM
310views Data Mining» more  KDD 2010»
13 years 10 months ago
An integrated machine learning approach to stroke prediction
Stroke is the third leading cause of death and the principal cause of serious long-term disability in the United States. Accurate prediction of stroke is highly valuable for early...
Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Ku...