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    BMCBI
    2006
    201views more  BMCBI 2006»
    Gene selection algorithms for microarray data based on least squares support vector machine
    13 years 9 months ago
    Gene selection algorithms for microarray data based on least squares support vector machine
    Download  www.biomedcentral.com
    Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
    E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
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    MCS
    2010
    Springer
    145views Pattern Recognition» more  MCS 2010»
    A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities
    13 years 7 months ago
    A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities
    Download  www.ee.surrey.ac.uk
    Abstract. The Support Kernel Machine (SKM) and the Relevance Kernel Machine (RKM) are two principles for selectively combining objectrepresentation modalities of different kinds b...
    Alexander Tatarchuk, Eugene Urlov, Vadim Mottl, Da...
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    BMCBI
    2010
    151views more  BMCBI 2010»
    Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
    13 years 9 months ago
    Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
    Download  www.biomedcentral.com
    Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...
    Zhanchao Li, Xuan Zhou, Zong Dai, Xiaoyong Zou
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    AAAI
    2006
    135views Intelligent Agents» more  AAAI 2006»
    Closest Pairs Data Selection for Support Vector Machines
    13 years 10 months ago
    Closest Pairs Data Selection for Support Vector Machines
    Download  www.aaai.org
    This paper presents data selection procedures for support vector machines (SVM). The purpose of data selection is to reduce the dataset by eliminating as many non support vectors ...
    Chaofan Sun
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    JMLR
    2006
    91views more  JMLR 2006»
    QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
    13 years 8 months ago
    QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
    Download  jmlr.csail.mit.edu
    We describe polynomial
    Don R. Hush, Patrick Kelly, Clint Scovel, Ingo Ste...
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