LIBSVM

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LIBSVM
Developer(s) Chih-Chung Chang and Chih-Jen Lin
Stable release
3.21 / December 14, 2015; 19 months ago (2015-12-14)
Written in Java, C++
Operating system Cross-platform
Type Machine Learning
License BSD
Website www.csie.ntu.edu.tw/~cjlin/libsvm

LIBSVM and LIBLINEAR are two popular open source machine learning libraries, both developed at the National Taiwan University and both written in C++ though with a C API. LIBSVM implements the SMO algorithm for kernelized support vector machines (SVMs), supporting classification and regression.[1] LIBLINEAR implements linear SVMs and logistic regression models trained using a coordinate descent algorithm.[2]

The SVM learning code from both libraries is often reused in other open source machine learning toolkits, including GATE, KNIME, Orange[3] and scikit-learn. Many bindings to it exist for programming languages such as Java, MATLAB and R.

Both libraries are free software released under the 3-clause BSD license.[4][5]

References[edit]

  1. ^ Chang, Chih-Chung; Lin, Chih-Jen (2011). "LIBSVM: A library for support vector machines". ACM Transactions on Intelligent Systems and Technology. 2 (3). 
  2. ^ R.-E. Fan; K.-W. Chang; C.-J. Hsieh; X.-R. Wang; C.-J. Lin (2008). "LIBLINEAR: A library for large linear classification". Journal of Machine Learning Research. 9: 1871–1874. 
  3. ^ Janez Demšar; Tomaž Curk; Aleš Erjavec; Črt Gorup; Tomaž Hočevar; Mitar Milutinovič; Martin Možina; Matija Polajnar; Marko Toplak; Anže Starič; Miha Stajdohar; Lan Umek; Lan Žagar; Jure Žbontar; Marinka Žitnik; Blaž Zupan (2013). "Orange: data mining toolbox in Python" (PDF). JMLR. 14 (1): 2349–2353. 
  4. ^ "COPYRIGHT". LIBSVM. National Taiwan University. 
  5. ^ "COPYRIGHT". LIBLINEAR. National Taiwan University. 

External links[edit]