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    KDD
    2004
    ACM
    139views Data Mining» more  KDD 2004»
    Learning a complex metabolomic dataset using random forests and support vector machines
    14 years 8 months ago
    Learning a complex metabolomic dataset using random forests and support vector machines
    Download  math.uc.edu
    Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
    Young Truong, Xiaodong Lin, Chris Beecher
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    ESANN
    2007
    103views Neural Networks» more  ESANN 2007»
    Interval discriminant analysis using support vector machines
    13 years 9 months ago
    Interval discriminant analysis using support vector machines
    Download  www.dice.ucl.ac.be
    Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernel...
    Cecilio Angulo, Davide Anguita, Luis Gonzál...
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    FGR
    2006
    IEEE
    297views Biometrics» more  FGR 2006»
    Automatic Skin Segmentation for Gesture Recognition Combining Region and Support Vector Machine Active Learning
    14 years 1 months ago
    Automatic Skin Segmentation for Gesture Recognition Combining Region and Support Vector Machine Active Learning
    Download  doras.dcu.ie
    Skin segmentation is the cornerstone of many applications such as gesture recognition, face detection, and objectionable image filtering. In this paper, we attempt to address the ...
    Junwei Han, George Awad, Alistair Sutherland, Hai ...
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    IJCNN
    2006
    IEEE
    146views Neural Networks» more  IJCNN 2006»
    Learning the Kernel in Mahalanobis One-Class Support Vector Machines
    14 years 1 months ago
    Learning the Kernel in Mahalanobis One-Class Support Vector Machines
    Download  www.cse.ust.hk
    — In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
    Ivor W. Tsang, James T. Kwok, Shutao Li
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    BIOINFORMATICS
    2006
    105views more  BIOINFORMATICS 2006»
    Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure
    13 years 7 months ago
    Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure
    Download  noble.gs.washington.edu
    Darrin P. Lewis, Tony Jebara, William Stafford Nob...
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