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BMCBI
2006
158views more  BMCBI 2006»
14 years 9 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
CSL
2006
Springer
14 years 9 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...
ML
2002
ACM
107views Machine Learning» more  ML 2002»
14 years 9 months ago
Training Invariant Support Vector Machines
Practical experience has shown that in order to obtain the best possible performance, prior knowledge about invariances of a classification problem at hand ought to be incorporated...
Dennis DeCoste, Bernhard Schölkopf
DATAMINE
1998
145views more  DATAMINE 1998»
14 years 9 months ago
A Tutorial on Support Vector Machines for Pattern Recognition
The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-...
Christopher J. C. Burges
DMIN
2009
132views Data Mining» more  DMIN 2009»
14 years 7 months ago
Understanding Support Vector Machine Classifications via a Recommender System-Like Approach
Support vector machines are a valuable tool for making classifications, but their black-box nature means that they lack the natural explanatory value that many other classifiers po...
David Barbella, Sami Benzaid, Janara M. Christense...