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APBC
2004
132views Bioinformatics» more  APBC 2004»
13 years 7 months ago
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
Liang Goh, Qun Song, Nikola K. Kasabov
ICIP
2008
IEEE
14 years 8 months ago
Using local regression kernels for statistical object detection
We present a novel approach to the problem of detection of visual similarity between a template image, and patches in a given image. The method is based on the computation of a lo...
Hae Jong Seo, Peyman Milanfar
BMCBI
2007
173views more  BMCBI 2007»
13 years 6 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
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...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
ECCV
2008
Springer
14 years 8 months ago
Local Regularization for Multiclass Classification Facing Significant Intraclass Variations
We propose a new local learning scheme that is based on the principle of decisiveness: the learned classifier is expected to exhibit large variability in the direction of the test ...
Lior Wolf, Yoni Donner
TMI
2010
151views more  TMI 2010»
13 years 29 days ago
Quantitative Analysis of Pulmonary Emphysema Using Local Binary Patterns
Abstract--We aim at improving quantitative measures of emphysema in computed tomography (CT) images of the lungs. Current standard measures, such as the relative area of emphysema ...
Lauge Sørensen, Saher B. Shaker, Marleen de...