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http://www.stat.purdue.edu/~yuzhu/stat598m3/Papers/NewSVM.pdf
New Support Vector Algorithms 1209 Figure 1: In SV regression, a desired accuracyeis speci” ed a priori.It is then attempted to ” t a tube with radiuseto the data.The trade-off between model
https://www.mitpressjournals.org/doi/10.1162/089976600300015565
Mar 13, 2006 · We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter ν lets one effectively control the number of support vectors.Cited by: 3132
https://www.researchgate.net/publication/12413257_New_Support_Vector_Algorithms
We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter nu lets one effectively control the number of support vectors.
https://www.deepdyve.com/lp/mit-press/new-support-vector-algorithms-4I2gUjGvJh
May 01, 2000 · New Support Vector Algorithms In these algorithms, a parameter ν lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other free parameters of the algorithm: the accuracy parameter ϵ in the regression case, and the regularization constant C in …
https://ieeexplore.ieee.org/document/6790203/citations
New Support Vector Algorithms Abstract: We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter ν lets one effectively control the number of support vectors.Cited by: 3132
https://papers.nips.cc/paper/1563-shrinking-the-tube-a-new-support-vector-regression-algorithm.pdf
Support Vector (SV) machines comprise a new class of learning algorithms, motivated by results of statistical learning theory (Vapnik, 1995). Originally developed for pattern recog nition, they represent the decision boundary in terms of a typically small subset (SchOikopf et aI., 1995) of all training examples, called the Support Vectors.
https://www.engineeringbigdata.com/support-vector-machine-algorithm/
The support vector machine is an algorithm that is primarily focused on detecting and analyzing relationships. This machine learning algorithm works by analyzing data sets through a series of variables. The way that the data respond to the variables can be mapped out.
https://www.sciencedirect.com/science/article/pii/S0893608009002019
Like the previous v -SVM, the proposed new support vector algorithms with parametric insensitive/margin model have the advantage of using the parameter 0 ≤ v ≤ 1 to control the number of support vectors. v -support vector regression algorithm v -support vector classification algorithm v is an upper bound on the fraction of errors.Cited by: 100
http://www.stat.purdue.edu/~yuzhu/stat598m3/Papers/NewSVM.pdf
New Support Vector Algorithms 1209 Figure 1: In SV regression, a desired accuracyeis speci” ed a priori.It is then attempted to ” t a tube with radiuseto the data.The trade-off between model
https://www.mitpressjournals.org/doi/10.1162/089976600300015565
Mar 13, 2006 · We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter ν lets one effectively control the number of support …Cited by: 3132
https://www.researchgate.net/publication/12413257_New_Support_Vector_Algorithms
We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter nu lets one effectively control the number of support vectors.
https://www.deepdyve.com/lp/mit-press/new-support-vector-algorithms-4I2gUjGvJh
May 01, 2000 · New Support Vector Algorithms In these algorithms, a parameter ν lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other free parameters of the algorithm: the accuracy parameter ϵ in the regression case, and the regularization constant C in …
https://ieeexplore.ieee.org/document/6790203/citations
New Support Vector Algorithms Abstract: We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter ν lets one effectively control the number of support vectors.Cited by: 3132
https://papers.nips.cc/paper/1563-shrinking-the-tube-a-new-support-vector-regression-algorithm.pdf
Support Vector (SV) machines comprise a new class of learning algorithms, motivated by results of statistical learning theory (Vapnik, 1995). Originally developed for pattern recog nition, they represent the decision boundary in terms of a typically small subset (SchOikopf et aI., 1995) of all training examples, called the Support Vectors.
https://www.engineeringbigdata.com/support-vector-machine-algorithm/
Few of these algorithms have the same utility, however, as the support vector machine. A support vector machine may not sound as simple or as straightforward as a decision tree or a linear regression algorithm.
https://www.sciencedirect.com/science/article/pii/S0893608009002019
Like the previous v-SVM, the proposed support vector algorithms have the advantage of using the parameter 0 ≤ v ≤ 1 for controlling the number of support vectors. To be more precise, v is an upper bound on the fraction of training errors and a lower bound on the fraction of support vectors. The algorithms are analyzed theoretically and ...Cited by: 100
http://www.stat.purdue.edu/~yuzhu/stat598m3/Papers/NewSVM.pdf
New Support Vector Algorithms 1209 Figure 1: In SV regression, a desired accuracyeis speci” ed a priori.It is then attempted to ” t a tube with radiuseto the data.The trade-off between model
https://www.mitpressjournals.org/doi/10.1162/089976600300015565
Mar 13, 2006 · We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter ν lets one effectively control the number of support …Cited by: 3132
https://www.researchgate.net/publication/12413257_New_Support_Vector_Algorithms
We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter nu lets one effectively control the number of support vectors.
https://ieeexplore.ieee.org/document/6790203/citations
Abstract: We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter ν lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other free parameters of the algorithm: the accuracy parameter ϵ in the ...Cited by: 3132
https://www.deepdyve.com/lp/mit-press/new-support-vector-algorithms-4I2gUjGvJh
May 01, 2000 · We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter ν lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other free parameters of the algorithm: the accuracy parameter ϵ in the regression ...
https://papers.nips.cc/paper/1563-shrinking-the-tube-a-new-support-vector-regression-algorithm.pdf
Shrinking the Tube: A New Support Vector Regression Algorithm 331 2 ZJ-SV REGRESSION AND c-SV REGRESSION To estimate functions (1) from empirical …
https://www.engineeringbigdata.com/support-vector-machine-algorithm/
In a support vector machine algorithm, nodes may be parts of the original function or different variables and categories used. There are a number of different approaches to learning that the support vector machine algorithm can perform. One of these is supervised learning.
https://www.researchgate.net/publication/26776492_New_support_vector_algorithms_with_parametric_insensitivemargin_model
In this paper, a modification of v-support vector machines (v-SVM) for regression and classification is described, and the use of a parametric insensitive/margin model with an arbitrary shape is ...
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