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http://pages.stat.wisc.edu/~wahba/ftp1/lee.lin.wahba.04.pdf
We propose the multicategory support vector machine (MSVM), which extends the binary SVM to the multicategory case and has good theoretical properties. The proposed method provides a unifying framework when there are either equal or unequal misclassi” cation costs.
https://www.tandfonline.com/doi/abs/10.1198/016214504000000098
Jan 24, 2012 · We propose the multicategory support vector machine (MSVM), which extends the binary SVM to the multicategory case and has good theoretical properties. The proposed method provides a unifying framework when there are either equal or unequal misclassification costs.Cited by: 904
https://www.semanticscholar.org/paper/Multicategory-Classification-by-Support-Vector-Bredensteiner-Bennett/09a807e7272f44e50398518665563f889c49bea6
We examine the problem of how to discriminate between objects of three or more classes. Specifically, we investigate how two-class discrimination methods can be extended to the multiclass case. We show how the linear programming (LP) approaches based on the work of Mangasarian and quadratic programming (QP) approaches based on Vapnik's Support Vector Machine (SVM) can be combined …
https://people.eecs.berkeley.edu/~jordan/papers/zhang-uai06.pdf
vector of 1’s, let Im denote the m m identity matrix, and let 0 denote the zero vector (or matrix) whose dimensionality is dependent upon the context. In ad-dition, A B represents the Kronecker product of A and B. 2.1 Multicategory Support Vector Machines The MSVM (Lee et al., 2004) is based on a c-tuple
http://pages.stat.wisc.edu/~myuan/papers/rsvm.final.pdf
Reinforced Multicategory Support Vector Machines Yufeng L IU and Ming YUAN Support vector machines are one of the most popular machine learning methods for classification. Despite its great success, the SVM was originally designed for binary classification. Extensions to the multicategory case are important for general classifica-tion problems.
http://www3.stat.sinica.edu.tw/statistica/oldpdf/a16n215.pdf
Support Vector Machines (SVMs), as powerful classi cation tools, have been widely used and proven e ective in binary classi cation. For multi-category clas-si cation, several versions of L2-norm multi-category SVMs (MSVMs) have been introduced, including Vapnik …
https://www.sciencedirect.com/science/article/pii/S0377221703007422
Linear programming approaches for multicategory support vector machines ... Features generated by KFDA could improve the performance of our linear programming approaches for multicategory classification, which will also be future research subjects. ... T. JoachimsText categorization with support vector machines: Learning with many relevant ...Cited by: 17
https://link.springer.com/article/10.1023/A:1008663629662
Specifically, we investigate how two-class discrimination methods can be extended to the multiclass case. We show how the linear programming (LP) approaches based on the work of Mangasarian and quadratic programming (QP) approaches based on Vapnik's Support Vector Machine (SVM) can be combined to yield two new approaches to the multiclass problem.Cited by: 457
http://proceedings.mlr.press/v2/liu07b/liu07b.pdf
The Support Vector Machine (SVM) has become one of the most popular ma-chine learning techniques in recent years. The success of the SVM is mostly due to its elegant margin concept and the-ory in binary classiflcation. Generaliza-tion to the multicategory setting, how-ever, is not trivial. There are a num-ber of difierent multicategory extensionsCited by: 76
https://www.sciencedirect.com/science/article/pii/S0952197619301538
Algorithm: Multi-category ternion support vector machine M-TerSVM is a supervised learning approach that builds a classifier model for K classes by using m training points. The procedure for generating M-TerSVM is explained in Algorithm 4.Author: Pooja Saigal, Suresh Chandra, Reshma Rastogi
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