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LIBSVM

Chih-Chung Chang; Chih‐Jen Lin · ACM Transactions on Intelligent Systems and Technology · 2011

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Author / responsible party
Chih-Chung Chang; Chih‐Jen Lin
Publisher
ACM Transactions on Intelligent Systems and Technology
Year
2011
Language
English

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LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popularity in machine learning and many other areas. In this article, we present all implementation details of LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.

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APA 7

Chang, C. C. & Lin, C. (2011). LIBSVM. https://doi.org/10.1145/1961189.1961199

MLA

Chang, Chih-Chung, and Chih‐Jen Lin. "LIBSVM." 2011. https://doi.org/10.1145/1961189.1961199.

Chicago

Chang, Chih-Chung and Chih‐Jen Lin. 2011. "LIBSVM.". https://doi.org/10.1145/1961189.1961199.

Harvard

Chang, C. C. and Lin, C. 2011, LIBSVM, ACM Transactions on Intelligent Systems and Technology, available at: https://doi.org/10.1145/1961189.1961199 [Accessed 6 Aug. 2026].

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Resource details

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Title
LIBSVM
Author / contributors
Chih-Chung Chang; Chih‐Jen Lin
Publisher
ACM Transactions on Intelligent Systems and Technology
Publication year
2011
Language
English

Subjects

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Computer science; Support vector machine; Popularity; Machine learning; Artificial intelligence; Selection (genetic algorithm); Convergence (economics); Multiclass classification; Data mining; Psychology; Economic growth; Social psychology
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