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    » A New Support Vector Machine for Data Mining
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    RSFDGRC
    2005
    Springer
    92views Data Mining» more  RSFDGRC 2005»
    Reducing the Storage Requirements of 1-v-1 Support Vector Machine Multi-classifiers
    13 years 10 months ago
    Reducing the Storage Requirements of 1-v-1 Support Vector Machine Multi-classifiers
    Download  www2.cs.uregina.ca
    Pawan Lingras, Cory J. Butz
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    KDD
    2002
    ACM
    160views Data Mining» more  KDD 2002»
    Scaling multi-class support vector machines using inter-class confusion
    14 years 5 months ago
    Scaling multi-class support vector machines using inter-class confusion
    Download  www.it.iitb.ac.in
    Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
    Shantanu Godbole, Sunita Sarawagi, Soumen Chakraba...
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    AUSDM
    2006
    Springer
    177views Data Mining» more  AUSDM 2006»
    On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
    13 years 8 months ago
    On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
    Download  crpit.com
    The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
    Tatjana Eitrich, Bruno Lang
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    ICDM
    2008
    IEEE
    99views Data Mining» more  ICDM 2008»
    Kernels for the Investigation of Localized Spatiotemporal Transitions of Drought with Support Vector Machines
    13 years 11 months ago
    Kernels for the Investigation of Localized Spatiotemporal Transitions of Drought with Support Vector Machines
    Download  idea.cs.ou.edu
    We present and discuss several spatiotemporal kernels designed to mine real-life and simulated data in support of drought prediction. We implement and empirically validate these k...
    Matthew W. Collier, Amy McGovern
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    PAKDD
    2005
    ACM
    111views Data Mining» more  PAKDD 2005»
    Training Support Vector Machines Using Greedy Stagewise Algorithm
    13 years 10 months ago
    Training Support Vector Machines Using Greedy Stagewise Algorithm
    Download  ttic.uchicago.edu
    Abstract. Hard margin support vector machines (HM-SVMs) have a risk of getting overfitting in the presence of the noise. Soft margin SVMs deal with this
    Liefeng Bo, Ling Wang, Licheng Jiao
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