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JSS
2008
317views more  JSS 2008»
14 years 11 months ago
Predicting defect-prone software modules using support vector machines
Effective prediction of defectprone software modules can enable software developers to focus quality assurance activities and allocate effort and resources more efficiently. Supp...
Karim O. Elish, Mahmoud O. Elish
IJON
2008
173views more  IJON 2008»
14 years 11 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
COLT
1999
Springer
15 years 4 months ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
CVPR
2004
IEEE
15 years 3 months ago
Learning in Region-Based Image Retrieval with Generalized Support Vector Machines
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
Iker Gondra, Douglas R. Heisterkamp
ICPR
2006
IEEE
16 years 25 days ago
Fast Support Vector Machine Classification using linear SVMs
We propose a classification method based on a decision tree whose nodes consist of linear Support Vector Machines (SVMs). Each node defines a decision hyperplane that classifies p...
Karina Zapien Arreola, Janis Fehr, Hans Burkhardt