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APBC
2004
132views Bioinformatics» more  APBC 2004»
13 years 9 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
BIBE
2007
IEEE
167views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Assessing the Performance of Macromolecular Sequence Classifiers
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
Cornelia Caragea, Jivko Sinapov, Vasant Honavar, D...
ICPR
2010
IEEE
13 years 12 months ago
Selection of Training Instances for Music Genre Classification
In this paper we present a method for the selection of training instances based on the classification accuracy of a SVM classifier. The instances consist of feature vectors repres...
Miguel Lopes, Fabien Gouyon, Alessandro Koerich, L...
ICPR
2006
IEEE
14 years 8 months ago
Ent-Boost: Boosting Using Entropy Measure for Robust Object Detection
Recently, boosting is used widely in object detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifiers which is on...
Duy-Dinh Le, Shin'ichi Satoh
BMCBI
2007
112views more  BMCBI 2007»
13 years 7 months ago
Selecting dissimilar genes for multi-class classification, an application in cancer subtyping
Background: Gene expression microarray is a powerful technology for genetic profiling diseases and their associated treatments. Such a process involves a key step of biomarker ide...
Zhipeng Cai, Randy Goebel, Mohammad R. Salavatipou...