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» Prediction of Contact Maps Using Support Vector Machines
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BMCBI
2008
169views more  BMCBI 2008»
13 years 8 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
PAKDD
2009
ACM
233views Data Mining» more  PAKDD 2009»
14 years 1 months ago
A Kernel Framework for Protein Residue Annotation
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...
ESANN
2006
13 years 9 months ago
Evolino for recurrent support vector machines
Abstract. We introduce a new class of recurrent, truly sequential SVM-like devices with internal adaptive states, trained by a novel method called EVOlution of systems with KErnel-...
Jürgen Schmidhuber, Matteo Gagliolo, Daan Wie...
CSL
2006
Springer
13 years 8 months ago
Support vector machines for speaker and language recognition
Support vector machines (SVMs) have proven to be a powerful technique for pattern classification. SVMs map inputs into a high dimensional space and then separate classes with a hy...
William M. Campbell, Joseph P. Campbell, Douglas A...
KAIS
2010
144views more  KAIS 2010»
13 years 6 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz