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https://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf
Keywords: Classi cation, LIBSVM, optimization, regression, support vector ma-chines, SVM 1 Introduction Support Vector Machines (SVMs) are a popular machine learning method for classi - cation, regression, and other learning tasks. Since the year 2000, we have been devel-oping the package LIBSVM as a library for support vector machines. The Web ...
https://www.csie.ntu.edu.tw/~cjlin/libsvm/
30 rows · References of LIBSVM: Official implementation document: C.-C. Chang and C.-J. Lin. …
https://dl.acm.org/doi/10.1145/1961189.1961199
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.
http://dns2.asia.edu.tw/~ysho/YSHO-English/1000%20Taiwan%20(Independent)/PDF/ACM%20Tra%20Int%20Sys%20Tec2,%2027.pdf
Support Vector Machines (SVMs) are a popular machine learning method for clas-sification, regression, and other learning tasks. Since the year 2000, we have been developing the package LIBSVM as a library for support vector machines.1 LIBSVM is currently one of the most widely used SVM software. In this article,2 we present all
https://www.researchgate.net/publication/228715647_LIBSVM_A_library_for_support_vector_machines
LIBSVM is a library for support vector machines (SVM) [31] which has gained wide popularity in machine learning and many other areas. A typical use of LIBSVM involves two steps: first, training a ...
https://www.deepdyve.com/lp/acm/libsvm-a-library-for-support-vector-machines-I3mx4LhVCN
Apr 01, 2011 · LIBSVM: A Library for Support Vector Machines CHIH-CHUNG CHANG and CHIH-JEN LIN, National Taiwan University 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 …
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.335.6184
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): 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.
https://github.com/arnaudsj/libsvm
LIBSVM -- A Library for Support Vector Machines (unofficial snapshot dist mirror) - arnaudsj/libsvm. LIBSVM -- A Library for Support Vector Machines (unofficial snapshot dist mirror) - arnaudsj/libsvm. ... ACM Transactions on Intelligent Systems and Technology, 2:27:1--27:27, 2011.
https://www.researchgate.net/publication/272623654_Libsvm
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.
https://scholar.google.com/citations?user=SLMkts8AAAAJ&hl=en
2011: LIBSVM: a Library for Support Vector Machines. C Chang, CJ Lin. 42932 * 2001: LIBSVM: A library for support vector machines. CC Chang, CJ Lin. ACM transactions on intelligent systems and technology (TIST) 2 (3), 27, 2011. 42913: 2011: LIBSVM: A library for support vector machines.
https://www.scirp.org/reference/ReferencesPapers.aspx?ReferenceID=1612106
Chang, C.C. and Lin, C.J. (2011) LIBSVM: A Library for Support Vector Machines. Acm T Intel Syst Tec, 2. has been cited by the following article: TITLE: Segmentation of Hyper-Acute Ischemic Infarcts from Diffusion Weighted Imaging Based on Support Vector Machine. AUTHORS: Yuqing Peng, Xiaodong Zhang, Qingmao Hu
https://en.wikipedia.org/wiki/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 Sequential minimal optimization (SMO) algorithm for kernelized support vector machines (SVMs), supporting classification and regression.
https://www.coursehero.com/file/p5j0ec0/Chang-CC-and-Lin-CJ-2011-LIBSVM-A-library-for-support-vector-machines-ACM/
Chang CC and Lin CJ 2011 LIBSVM A library for support vector machines ACM from PHYSICS PHYS 2002 at Universiti Teknologi Mara
http://www.sciepub.com/reference/30905
Chang, C.C. and Lin, C. J., “LIBSVM: a library for support vector machines,” ACM Transactions on Intelligent Systems and Technology (TIST), 2(3), 2011. has been cited by the following article: Article
https://github.com/faruto/Libsvm-FarutoUltimate-Version/blob/master/Libsvm-FarutoUltimate%20V3.1/matlab-implement%5Bby%20faruto%5D/TutorialTest.m
Libsvm-FarutoUltimate Version. Contribute to faruto/Libsvm-FarutoUltimate-Version development by creating an account on GitHub.
https://www.scirp.org/reference/referencespapers.aspx?referenceid=2323477
Chang, C.-C. and Lin, C.-J. (2011) Libsvm A Library for Support Vector Machines. ACM Transactions on Intelligent Systems and Technology, 2, 27.
https://dblp.uni-trier.de/rec/journals/tist/ChangL11
Bibliographic details on LIBSVM: A library for support vector machines.
http://www.sciepub.com/reference/138080
C. C. Chang, C.-J. Lin., LIBSVM, a library for support vector machines, ACM Transactions on Intelligent Systems and Technology, 2:27: 1-27:27, (2011). has been cited by the following article: Article. Diagnostics of Product Defects by Clustering and Machine Learning Classification Algorithm.
https://omictools.com/libsvm-tool
Supports vector classification, regression and distribution estimation. LIBSVM solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM classification. It also supports multi-class classification. A typical use of LIBSVM involves two steps: (i) training a dataset to obtain a ...
http://jmlr.csail.mit.edu/papers/volume15/claesen14a/claesen14a.pdf
EnsembleSVM: A Library for Ensemble Learning Using Support Vector Machines Marc Claesen [email protected] KU Leuven, ESAT { STADIUS/iMinds Future Health Kasteelpark Arenberg 10, box 2446 3001 Leuven, Belgium Frank De Smet [email protected] KU Leuven, Department of Public Health and Primary Care, Environment and Health
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