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    KAIS
    2006
    121views more  KAIS 2006»
    Using discriminant analysis for multi-class classification: an experimental investigation
    14 years 9 months ago
    Using discriminant analysis for multi-class classification: an experimental investigation
    Download  users.cis.fiu.edu
    Abstract. Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the...
    Tao Li, Shenghuo Zhu, Mitsunori Ogihara
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    CVPR
    2006
    IEEE
    609views Computer Vision» more  CVPR 2006»
    SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
    15 years 11 months ago
    SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
    Download  www.cs.berkeley.edu
    We consider visual category recognition in the framework of measuring similarities, or equivalently perceptual distances, to prototype examples of categories. This approach is qui...
    Alexander C. Berg, Hao Zhang 0003, Jitendra Malik,...
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    RECOMB
    2005
    Springer
    147views Computational Biology» more  RECOMB 2005»
    Learning Interpretable SVMs for Biological Sequence Classification
    15 years 10 months ago
    Learning Interpretable SVMs for Biological Sequence Classification
    Download  eprints.pascal-network.org
    Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
    Christin Schäfer, Gunnar Rätsch, Sö...
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    JMLR
    2006
    150views more  JMLR 2006»
    Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
    14 years 9 months ago
    Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
    Download  jmlr.csail.mit.edu
    Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian, 2000; Bradley and Mangasarian, 1998), are formulated here as a completely unconstra...
    Olvi L. Mangasarian
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    KDD
    2004
    ACM
    163views Data Mining» more  KDD 2004»
    A Novel Approach for Prediction of Protein Subcellular Localization from Sequence Using Fourier Analysis and Support Vector Mach
    15 years 10 months ago
    A Novel Approach for Prediction of Protein Subcellular Localization from Sequence Using Fourier Analysis and Support Vector Mach
    Download  array.bioengr.uic.edu
    Zhengdeng Lei, Yang Dai
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