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A Simpler Approach to Coefficient Regularized Support Vector Machines Regression

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Listed:
  • Hongzhi Tong
  • Di-Rong Chen
  • Fenghong Yang

Abstract

We consider a kind of support vector machines regression (SVMR) algorithms associated with lq (1 ≤ q

Suggested Citation

  • Hongzhi Tong & Di-Rong Chen & Fenghong Yang, 2014. "A Simpler Approach to Coefficient Regularized Support Vector Machines Regression," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:206015
    DOI: 10.1155/2014/206015
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    References listed on IDEAS

    as
    1. Dao-Hong Xiang & Ting Hu & Ding-Xuan Zhou, 2012. "Approximation Analysis of Learning Algorithms for Support Vector Regression and Quantile Regression," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-17, February.
    2. Dao-Hong Xiang & Ting Hu & Ding-Xuan Zhou, 2012. "Approximation Analysis of Learning Algorithms for Support Vector Regression and Quantile Regression," Journal of Applied Mathematics, John Wiley & Sons, vol. 2012(1).
    Full references (including those not matched with items on IDEAS)

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