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» Data Mining via Support Vector Machines
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IJON
2008
173views more  IJON 2008»
14 years 9 months ago
Support vector machine classification for large data sets via minimum enclosing ball clustering
Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitabl...
Jair Cervantes, Xiaoou Li, Wen Yu, Kang Li
ICDM
2006
IEEE
118views Data Mining» more  ICDM 2006»
15 years 3 months ago
Generalizing Version Space Support Vector Machines for Non-Separable Data
Although version space support vector machines (VSSVMs) are a successful approach to reliable classification [6], they are restricted to separable data. This paper proposes gener...
Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, Ni...
WINE
2005
Springer
268views Economy» more  WINE 2005»
15 years 3 months ago
Mining Stock Market Tendency Using GA-Based Support Vector Machines
In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...
Lean Yu, Shouyang Wang, Kin Keung Lai
PAMI
2006
128views more  PAMI 2006»
14 years 9 months ago
Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues
A new approach to support vector machine (SVM) classification is proposed wherein each of two data sets are proximal to one of two distinct planes that are not parallel to each oth...
Olvi L. Mangasarian, Edward W. Wild
SIGKDD
2000
139views more  SIGKDD 2000»
14 years 9 months ago
Support Vector Machines: Hype or Hallelujah?
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
Kristin P. Bennett, Colin Campbell