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Description: 该工具箱包括了二种分类,二种回归,以及一种一类支持向量机算法-The toolkit includes two kinds of classification, two kinds of return, and a one-class support vector machine algorithm
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Size: 12288 |
Author: Lee Joan |
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Description: smo算法是与svr（支持向量机回归）和svc（支持向量机分类）具有相似数学形式，并在此基础上提出的一种用于SVR的简化算法。-smo algorithm is svr (support vector machine regression) and svc (SVM) with similar mathematical form, and puts forward a simplified algorithm for SVR.
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Size: 1024 |
Author: heyufeng |
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Description: SMO算法的m文件以及用svr测试该算法的m文件，以及smo算法文档详细介绍及使用说明-The SMO algorithm m file and test the algorithm using SVR m files, as well as the SMO algorithm document details and instructions
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Size: 632832 |
Author: ivy |
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Description: 这个是用SMO算法做的支持向量回归程序，有测试程序-support vector regression with SMO algorithm
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Size: 4152320 |
Author: hqh |
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Description: 这个是用SMO算法做的支持向量回归程序，语言是JAVA-This is done using the SMO support vector regression algorithm, language is JAVA
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Size: 5120 |
Author: 越南男 |
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Description: 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.
Since version 2.8, it implements an SMO-type algorithm proposed in this paper:
R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using second order information for training SVM. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there. (how to cite LIBSVM)
Our goal is to help users other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include-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.
Since version 2.8, it implements an SMO-type algorithm proposed in this paper:
R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using second order information for training SVM. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there. (how to cite LIBSVM)
Our goal is to help users other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include
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Size: 1321984 |
Author: carl2380 |
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Description: libsvm-3.22.rar 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.
Since version 2.8, it implements an SMO-type algorithm proposed in this paper:
R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using second order information for training SVM. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there. (how to cite LIBSVM)
Our goal is to help users other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include-libsvm-3.22.rar 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.
Since version 2.8, it implements an SMO-type algorithm proposed in this paper:
R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using second order information for training SVM. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there. (how to cite LIBSVM)
Our goal is to help users other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include
Platform: |
Size: 839680 |
Author: carl2380 |
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