DocumentCode :
2211369
Title :
A View of Support Vector Machines Algorithm on Classification Problems
Author :
Jing, Ranzhe ; Zhang, Yong
Author_Institution :
Sch. of Inf. Manage. & Eng., Shanghai Univ. of Finance & Econ., Shanghai, China
fYear :
2010
fDate :
7-8 Aug. 2010
Firstpage :
13
Lastpage :
16
Abstract :
Support vector machine (SVM) algorithm has shown a good learning ability and generalization ability in classification, regression and forecasting. This paper mainly analyzes the the performance of support vector machine algorithm in the classification problem, including the algorithm in the kernel function selection, parameter optimization, and integration of other algorithms and to deal with multi-classification issues improvements. Concludes with a discussion of the SVM algorithm is the direction of further improvement.
Keywords :
generalisation (artificial intelligence); optimisation; parameter estimation; pattern classification; support vector machines; SVM algorithm; classification problem; generalization ability; kernel function selection; multiclassification issue; parameter optimization; support vector machine; Classification algorithm; Genetic algorithm; Parameter Optimization; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Communications (Mediacom), 2010 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-0-7695-4136-5
Type :
conf
DOI :
10.1109/MEDIACOM.2010.21
Filename :
5694130
Link To Document :
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