66 search results - page 2 / 14 » Learning Sparse SVM for Feature Selection on Very High Dimen... |
ICDM
2008
IEEE
13 years 11 months ago
2008
IEEE
In this paper, we propose the "Democratic Classifier", a simple, democracy-inspired patternbased classification algorithm that uses very short patterns for classificatio...
PAMI
2010
13 years 3 months ago
2010
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
ECCV
2010
Springer
13 years 9 months ago
2010
Springer
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
BMCBI
2007
13 years 4 months ago
2007
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
PKDD
2009
Springer
13 years 11 months ago
2009
Springer
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...