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» Response modeling with support vector machines
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BMCBI
2007
127views more  BMCBI 2007»
14 years 9 months ago
Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines
Background: Human genetic variations primarily result from single nucleotide polymorphisms (SNPs) that occur approximately every 1000 bases in the overall human population. The no...
Jian Tian, Ningfeng Wu, Xuexia Guo, Jun Guo, Juhua...
KES
2008
Springer
14 years 9 months ago
Downsizing Multigenic Predictors of the Response to Preoperative Chemotherapy in Breast Cancer
We present a method for designing efficient multigenic predictors with few probes and its application to the prediction of the response to preoperative chemotherapy in breast cance...
René Natowicz, Roberto Incitti, Roman Rouzi...
CSDA
2010
133views more  CSDA 2010»
14 years 7 months ago
Optimized fixed-size kernel models for large data sets
A modified active subset selection method based on quadratic R
Kris De Brabanter, Jos De Brabanter, Johan A. K. S...
EUSFLAT
2009
132views Fuzzy Logic» more  EUSFLAT 2009»
14 years 7 months ago
Modeling Position Specificity in Sequence Kernels by Fuzzy Equivalence Relations
This paper demonstrates that several known sequence kernels can be expressed in a unified framework in which the position specificity is modeled by fuzzy equivalence relations. In ...
Ulrich Bodenhofer, Karin Schwarzbauer, Mihaela Ion...
ICML
2001
IEEE
15 years 10 months ago
A Unified Loss Function in Bayesian Framework for Support Vector Regression
In this paper, we propose a unified non-quadratic loss function for regression known as soft insensitive loss function (SILF). SILF is a flexible model and possesses most of the d...
Wei Chu, S. Sathiya Keerthi, Chong Jin Ong