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» Optimal feature selection for support vector machines
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BMCBI
2006
146views more  BMCBI 2006»
15 years 4 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»
15 years 10 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
15 years 11 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»
15 years 10 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»
16 years 4 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