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» Two-dimensional solution path for support vector regression
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BMCBI
2006
211views more  BMCBI 2006»
13 years 5 months ago
Missing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding s
Background: Gene expression profiling has become a useful biological resource in recent years, and it plays an important role in a broad range of areas in biology. The raw gene ex...
Xian Wang, Ao Li, Zhaohui Jiang, Huanqing Feng
NPL
2006
98views more  NPL 2006»
13 years 5 months ago
Lamb Meat Quality Assessment by Support Vector Machines
The correct assessment of meat quality (i.e., to fulfill the consumer's needs) is crucial element within the meat industry. Although there are several factors that affect the ...
Paulo Cortez, Manuel Portelinha, Sandra Rodrigues,...
ICML
2007
IEEE
14 years 6 months ago
A kernel path algorithm for support vector machines
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
NIPS
2004
13 years 6 months ago
The Entire Regularization Path for the Support Vector Machine
The support vector machine (SVM) is a widely used tool for classification. Many efficient implementations exist for fitting a two-class SVM model. The user has to supply values fo...
Trevor Hastie, Saharon Rosset, Robert Tibshirani, ...
CDC
2009
IEEE
180views Control Systems» more  CDC 2009»
13 years 8 months ago
Robustness analysis for Least Squares kernel based regression: an optimization approach
—In kernel based regression techniques (such as Support Vector Machines or Least Squares Support Vector Machines) it is hard to analyze the influence of perturbed inputs on the ...
Tillmann Falck, Johan A. K. Suykens, Bart De Moor