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» Optimal feature selection for support vector machines
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BMCBI
2006
146views more  BMCBI 2006»
13 years 8 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara
BIBE
2007
IEEE
142views Bioinformatics» more  BIBE 2007»
14 years 2 months ago
An HV-SVM Classifier to Infer TF-TF Interactions Using Protein Domains and GO Annotations
—Interactions between transcription factors (TFs) are necessary for deciphering the complex mechanisms of transcription regulation in eukaryotes. In this paper, we proposed a nov...
Xiaoli Li, Jun-Xiang Lee, Bharadwaj Veeravalli, Se...
ICML
2009
IEEE
14 years 2 months ago
Non-monotonic feature selection
We consider the problem of selecting a subset of m most informative features where m is the number of required features. This feature selection problem is essentially a combinator...
Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, ...
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
14 years 1 months ago
Is negative selection appropriate for anomaly detection?
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
14 years 8 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee