支持向量机 Support Vector Machine 程序网址

               

（1）Least Squares Support Vector Machines (LS-SVM)

http://www.esat.kuleuven.be/sista/lssvmlab/

Support Vector Machines is a powerful methodology for solving problems in nonlinear classification, function estimation and density estimation which has also led to many other recent developments in kernel based methods in general.

         

Latest version: LS-SVMlab v1.8 (August 16, 2011)

Book reference:
J.A.K. Suykens, T. Van Gestel, J. De Brabanter, B. De Moor, J. Vandewalle, Least Squares Support Vector Machines, World Scientific, Singapore, 2002 (ISBN 981-238-151-1)

             

"Learning with primal and dual model representations: a unifying picture": plenary talk ICASSP 2016, Shanghai: [pdf]

"SVD meets LS-SVM: a unifying picture": invited seminar at UCL, LLN 2015: [pdf]

             

                     

（2）LIBSVM -- A Library for Support Vector Machines

Chih-Chung Chang and Chih-Jen Lin

http://www.csie.ntu.edu.tw/~cjlin/libsvm/

LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.

• Python, R, MATLAB, Perl, Ruby, Weka, Common LISP, CLISP, Haskell, OCaml, LabVIEW, and PHP interfaces. C# .NET code and CUDA extension is available.
  It's also included in some data mining environments: RapidMiner, PCP, and LIONsolver.

         

           

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