Support vector machines

被引：133
|
作者：
Guenther, Nick [1 ,2 ]
Schonlau, Matthias [3 ]
机构：
[1] Univ Waterloo, Dept Stat, Waterloo, ON, Canada
[2] Univ Waterloo, Sch Comp Sci, Waterloo, ON, Canada
[3] Univ Waterloo, Dept Stat & Actuarial Sci, Waterloo, ON, Canada
来源：
STATA JOURNAL | 2016年 / 16卷 / 04期
关键词：
st0461; svmachines; svm; statistical learning; machine learning; support vector machines; TUTORIAL;
D O I：
10.1177/1536867X1601600407
中图分类号：
O1 [数学]; C [社会科学总论];
学科分类号：
03 ; 0303 ; 0701 ; 070101 ;
摘要：
Support vector machines are statistical-and machine-learning techniques with the primary goal of prediction. They can be applied to continuous, binary, and categorical outcomes analogous to Gaussian, logistic, and multinomial regression. We introduce a new command for this purpose, svmachines. This package is a thin wrapper for the widely deployed libsvm (Chang and Lin, 2011, ACM Transactions on Intelligent Systems and Technology 2(3): Article 27). We illustrate svmachines with two examples.
引用
收藏
页码：917 / 937
页数：21
相关论文
共 50 条
  • [31] Properties of support vector machines
    Pontil, M
    Verri, A
    NEURAL COMPUTATION, 1998, 10 (04) : 955 - 974
  • [32] Catenary Support Vector Machines
    Kan, Kin Fai
    Shelton, Christian R.
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PART I, PROCEEDINGS, 2008, 5211 : 597 - 610
  • [33] Distributed support vector machines
    Navia-Vazquez, A.
    Gutierrez-Gonzalez, D.
    Parrado-Hernandez, E.
    Navarro-Abellan, J. J.
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2006, 17 (04): : 1091 - 1097
  • [34] Field Support Vector Machines
    Huang, Kaizhu
    Jiang, Haochuan
    Zhang, Xu-Yao
    IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE, 2017, 1 (06): : 454 - 463
  • [35] Optimisation on support vector machines
    Pedroso, JP
    Murata, N
    IJCNN 2000: PROCEEDINGS OF THE IEEE-INNS-ENNS INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOL VI, 2000, : 399 - 404
  • [36] Selective support vector machines
    Seref, Onur
    Kundakcioglu, O. Erhun
    Prokopyev, Oleg A.
    Pardalos, Panos M.
    JOURNAL OF COMBINATORIAL OPTIMIZATION, 2009, 17 (01) : 3 - 20
  • [37] Sparseness of support vector machines
    Steinwart, I
    JOURNAL OF MACHINE LEARNING RESEARCH, 2004, 4 (06) : 1071 - 1105
  • [38] An introduction to support vector machines
    Schölkopf, B
    RECENT ADVANCES AND TRENDS IN NONPARAMETRIC STATISTICS, 2003, : 3 - 17
  • [39] Faster Support Vector Machines
    Schlag S.
    Schmitt M.
    Schulz C.
    ACM Journal of Experimental Algorithmics, 2021, 26
  • [40] Binarized Support Vector Machines
    Carrizosa, Emilio
    Martin-Barragan, Belen
    Morales, Dolores Romero
    INFORMS JOURNAL ON COMPUTING, 2010, 22 (01) : 154 - 167
12345