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COLT
1999
Springer
15 years 1 months ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
TITB
2008
102views more  TITB 2008»
14 years 9 months ago
Nonlinear Support Vector Machine Visualization for Risk Factor Analysis Using Nomograms and Localized Radial Basis Function Kern
Nonlinear classifiers, e.g., support vector machines (SVMs) with radial basis function (RBF) kernels, have been used widely for automatic diagnosis of diseases because of their hig...
Baek Hwan Cho, Hwanjo Yu, Jong Shill Lee, Young Jo...
BMCBI
2005
155views more  BMCBI 2005»
14 years 9 months ago
Mining protein function from text using term-based support vector machines
Background: Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We...
Simon B. Rice, Goran Nenadic, Benjamin J. Stapley
AIME
2007
Springer
15 years 3 months ago
Predictive Modeling of fMRI Brain States Using Functional Canonical Correlation Analysis
We present a novel method for predictive modeling of human brain states from functional neuroimaging (fMRI) data. Extending the traditional canonical correlation analysis of discre...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
IJON
2006
119views more  IJON 2006»
14 years 9 months ago
Support vector machine for functional data classification
Abstract. Functional data analysis is a growing research field and numerous works present a generalization of the classical statistical methods to function classification or regres...
Fabrice Rossi, Nathalie Villa