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LIBSVM: A library for support vector machines
Abstract
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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Metadata
- Authors
- Chang, C.-C., & Lin, C.-J.
- Affiliations
- National Taiwan University (TW)
- ORCID
- Lin, Chih-Jen
- Venue
- ACM Transactions on Intelligent Systems and Technology
- Published
- 2011-04
- Volume
- 2
- Issue
- 3
- Pages
- 1-27
- ISSN
- 2157-6904 (ISSN-L)
- 2157-6912
- OpenAlex
- W2153635508
- Cited by
- 40,918
- References
- 55
- Citations by year
- 2026: 462 · 2025: 825 · 2024: 916 · 2023: 1155 · 2022: 1487 · 2021: 1910 · 2020: 2233 · 2019: 2526 · 2018: 2850 · 2017: 3142 · 2016: 3468 · 2015: 3562 · 2014: 3302 · 2013: 2936 · 2012: 2306
- FWCI
- 3060.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Transactions on Intelligent Systems and Technology (publishedVersion)
- Funders
- National Science Council Taiwan (NSC 89-2213-E-002-013NSC 89-2213-E-002-106)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Algorithms
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and ELM
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Data Classification
- Keywords
- LIBSVM, support vector machine, convergence analysis, multi-class classification, probability estimates, parameter selection, software implementation
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