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» Optimal feature selection for support vector machines
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ARTMED
2007
347views more  ARTMED 2007»
13 years 8 months ago
A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature
Objective: This study investigates the use of automated pattern recognition methods on magnetic resonance data with the ultimate goal to assist clinicians in the diagnosis of brai...
Jan Luts, Arend Heerschap, Johan A. K. Suykens, Sa...
CEC
2007
IEEE
14 years 2 months ago
Concerning the potential of evolutionary support vector machines
— Within the present paper, we put forward a novel hybridization between support vector machines and evolutionary algorithms. Evolutionary support vector machines consider the cl...
Ruxandra Stoean, Mike Preuss, Catalin Stoean, Dumi...
EVOW
2006
Springer
13 years 11 months ago
Robust SVM-Based Biomarker Selection with Noisy Mass Spectrometric Proteomic Data
Abstract. Computational analysis of mass spectrometric (MS) proteomic data from sera is of potential relevance for diagnosis, prognosis, choice of therapy, and study of disease act...
Elena Marchiori, Connie R. Jimenez, Mikkel West-Ni...
MICCAI
2004
Springer
14 years 8 months ago
SVM Optimization for Hyperspectral Colon Tissue Cell Classification
The classification of normal and malginant colon tissue cells is crucial to the diagnosis of colon cancer in humans. Given the right set of feature vectors, Support Vector Machines...
Kashif Rajpoot, Nasir Rajpoot
JCB
2006
138views more  JCB 2006»
13 years 7 months ago
Recognition and Classification of Histones Using Support Vector Machine
Histones are DNA-binding proteins found in the chromatin of all eukaryotic cells. They are highly conserved and can be grouped into five major classes: H1/H5, H2A, H2B, H3, and H4...
Manoj Bhasin, Ellis L. Reinherz, Pedro A. Reche