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http://pages.stat.wisc.edu/~wahba/ftp1/lee.lin.wahba.04.pdf
Multicategory Support Vector Machines: Theory and Application to the Classi” cation of Microarray Data and Satellite Radiance Data YoonkyungLEE,YiLIN,andGraceWAHBA Two-category support vector machines (SVM) have been very popular in the machine learning community for classi” cation problems.
https://www.tandfonline.com/doi/abs/10.1198/016214504000000098
Jan 24, 2012 · Multicategory Support Vector Machines Theory and Application to the Classification of Microarray Data and Satellite Radiance Data Yoonkyung Lee Yoonkyung Lee is Assistant Professor, Department of Statistics, The Ohio State University, Columbus, OH 43210 .Cited by: 904
https://www.researchgate.net/publication/2482777_Multicategory_Support_Vector_Machines_Theory_and_Application_to_the_Classification_of_Microarray_Data_and_Satellite_Radiance_Data
Multicategory Support Vector Machines, Theory, and Application to the Classification of Microarray Data and Satellite Radiance Data. ... We have proposed the Multicategory Support Vector Machine ...
https://ideas.repec.org/a/bes/jnlasa/v99y2004p67-81.html
"Multicategory Support Vector Machines: Theory and Application to the Classification of Microarray Data and Satellite Radiance Data," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 67-81, January.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.7912
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Two category Support Vector Machines (SVM) have been very popular in the machine learning community for the classi cation problem. Solving multicategory problems by a series of binary classi ers is quite common in the SVM paradigm. However, this approach may fail under a variety of circumstances.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.87.191
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): The Support Vector Machine (SVM) has shown great performance in practice as a classification methodology. Oftentimes multicategory problems have been treated as a series of binary problems in the SVM paradigm. Even though the SVM implements the optimal classification rule asymptotically in the binary case, solutions ...
https://link.springer.com/book/10.1007/b95439
The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.3358
BibTeX @MISC{Lee02multicategorysupport, author = {Yoonkyung Lee and Cheol-koo Lee and Yoonkyung Lee and Cheol-koo Lee}, title = {Multicategory support vector machines, theory, and application to the classification of microarray data and satellite …
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
https://www.researchgate.net/publication/221621494_Support_Vector_Machines_Theory_and_Applications
This chapter presents a summary of the issues discussed during the one day workshop on ”Support Vector Machines (SVM) Theory and Applications” organized as part of the Advanced Course on ...
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