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» Applying Support Vector Machines to Imbalanced Datasets
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ISMB
2001
13 years 10 months ago
Molecular classification of multiple tumor types
Using gene expression data to classify tumor types is a very promising tool in cancer diagnosis. Previous works show several pairs of tumor types can be successfully distinguished...
Chen-Hsiang Yeang, Sridhar Ramaswamy, Pablo Tamayo...
BMCBI
2005
120views more  BMCBI 2005»
13 years 9 months ago
pSLIP: SVM based protein subcellular localization prediction using multiple physicochemical properties
Background: Protein subcellular localization is an important determinant of protein function and hence, reliable methods for prediction of localization are needed. A number of pre...
Deepak Sarda, Gek Huey Chua, Kuo-Bin Li, Arun Kris...
MICCAI
2003
Springer
14 years 10 months ago
Morphometric Analysis of Brain Structures for Improved Discrimination
Abstract. We perform discriminative analysis of brain structures using morphometric information. Spherical harmonics technique and point distribution model are used for shape descr...
Li Shen, James Ford, Fillia Makedon, Yuhang Wang, ...
ISM
2008
IEEE
156views Multimedia» more  ISM 2008»
14 years 3 months ago
Correlation-Based Video Semantic Concept Detection Using Multiple Correspondence Analysis
Semantic concept detection has emerged as an intriguing topic in multimedia research recently. The ability to interpret high-level semantics from low-level features has been the l...
Lin Lin, Guy Ravitz, Mei-Ling Shyu, Shu-Ching Chen
TIP
2008
175views more  TIP 2008»
13 years 9 months ago
Customizing Kernel Functions for SVM-Based Hyperspectral Image Classification
Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available ...
Baofeng Guo, Steve R. Gunn, Robert I. Damper, Jame...