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    ICMLA
    2004
    129views Machine Learning» more  ICMLA 2004»
    Income prediction via support vector machine
    13 years 6 months ago
    Income prediction via support vector machine
    Download  www.cis.ysu.edu
    Alina Lazar
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    JMLR
    2008
    110views more  JMLR 2008»
    Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers
    13 years 4 months ago
    Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers
    Download  jmlr.csail.mit.edu
    Support vector machine (SVM) is one of the most popular and promising classification algorithms. After a classification rule is constructed via the SVM, it is essential to evaluat...
    Bo Jiang, Xuegong Zhang, Tianxi Cai
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    BMCBI
    2010
    159views more  BMCBI 2010»
    Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
    13 years 4 months ago
    Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
    Download  www.biomedcentral.com
    Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...
    Alvaro J. González, Li Liao
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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 4 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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    TITB
    2008
    102views more  TITB 2008»
    Nonlinear Support Vector Machine Visualization for Risk Factor Analysis Using Nomograms and Localized Radial Basis Function Kern
    13 years 4 months ago
    Nonlinear Support Vector Machine Visualization for Risk Factor Analysis Using Nomograms and Localized Radial Basis Function Kern
    Download  hwanjoyu.org
    Nonlinear classifiers, e.g., support vector machines (SVMs) with radial basis function (RBF) kernels, have been used widely for automatic diagnosis of diseases because of their hig...
    Baek Hwan Cho, Hwanjo Yu, Jong Shill Lee, Young Jo...
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