Regularized least squares support vector regression for the simultaneous learning of a function and its derivatives

被引：27
|
作者：
Jayadeva [2 ]
Khemchandani, Reshma [1 ]
Chandra, Suresh [1 ]
机构：
[1] Indian Inst Technol, Dept Math, New Delhi 110016, India
[2] Inst Area Vasant Kunj, IBM India Res Lab, New Delhi 110070, India
来源：
INFORMATION SCIENCES | 2008年 / 178卷 / 17期
关键词：
support vector machines; regularized least squares; machine learning; function approximation;
D O I：
10.1016/j.ins.2008.04.007
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
in this paper, we propose a regularized least squares approach based support vector machine for simultaneously approximating a function and its derivatives. The proposed algorithm is simple and fast as no quadratic programming solver needs to be employed. Effectively, only the solution of a structured system of linear equations is needed. (c) 2008 Published by Elsevier Inc.
引用
收藏
页码：3402 / 3414
页数：13
相关论文
共 50 条
  • [21] Primal least squares twin support vector regression
    Huang, Hua-juan
    Ding, Shi-fei
    Shi, Zhong-zhi
    JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE C-COMPUTERS & ELECTRONICS, 2013, 14 (09): : 722 - 732
  • [22] Complete subset least squares support vector regression
    Qiu, Yue
    ECONOMICS LETTERS, 2021, 200
  • [23] Primal least squares twin support vector regression
    Huang, Hua-Juan
    Ding, Shi-Fei
    Shi, Zhong-Zhi
    Journal of Zhejiang University: Science C, 2013, 14 (09): : 722 - 732
  • [24] Mapped least squares support vector machine regression
    Zheng, S
    Sun, YQ
    Tian, JW
    Liu, J
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2005, 19 (03) : 459 - 475
  • [25] Primal least squares twin support vector regression
    Hua-juan Huang
    Shi-fei Ding
    Zhong-zhi Shi
    Journal of Zhejiang University SCIENCE C, 2013, 14 : 722 - 732
  • [26] Recursive reduced least squares support vector regression
    Zhao, Yongping
    Sun, Jianguo
    PATTERN RECOGNITION, 2009, 42 (05) : 837 - 842
  • [27] Regularized Total Least Squares Broad Learning System for Regression
    Xiong, Ke-Jia
    Yang, Guan-Ci
    Zhou, Tao
    Xie, Zhen-Qiang
    Journal of Computers (Taiwan), 2025, 36 (01) : 89 - 112
  • [28] A robust weighted least squares support vector regression based on least trimmed squares
    Chen, Chuanfa
    Yan, Changqing
    Li, Yanyan
    NEUROCOMPUTING, 2015, 168 : 941 - 946
  • [29] Regularized robust fuzzy least squares twin support vector machine for class imbalance learning
    Ganaie, M. A.
    Tanveer, M.
    Suganthan, P. N.
    2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2020,
  • [30] Simultaneous chemiluminescence determination of amoxicillin and clavulanic acid using least squares support vector regression
    Hasanpour, F.
    Ensafi, Ali A.
    Khayamian, T.
    ANALYTICA CHIMICA ACTA, 2010, 670 (1-2) : 44 - 50
12345