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» Response modeling with support vector machines
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JSS
2008
317views more  JSS 2008»
14 years 9 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
ICANN
2005
Springer
15 years 3 months ago
Training of Support Vector Machines with Mahalanobis Kernels
Abstract. Radial basis function (RBF) kernels are widely used for support vector machines. But for model selection, we need to optimize the kernel parameter and the margin paramete...
Shigeo Abe
PRICAI
2004
Springer
15 years 2 months ago
Prediction of the Risk Types of Human Papillomaviruses by Support Vector Machines
Abstract. Infection by high-risk human papillomaviruses (HPVs) is associated with the development of cervical cancers. Classification of risk types is important to understand the ...
Je-Gun Joung, Sok June Oh, Byoung-Tak Zhang
MCS
2005
Springer
15 years 3 months ago
Half-Against-Half Multi-class Support Vector Machines
A Half-Against-Half (HAH) multi-class SVM is proposed in this paper. Unlike the commonly used One-Against-All (OVA) and One-Against-One (OVO) implementation methods, HAH is built ...
Hansheng Lei, Venu Govindaraju
ML
2002
ACM
223views Machine Learning» more  ML 2002»
14 years 9 months ago
Text Categorization with Support Vector Machines. How to Represent Texts in Input Space?
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequenc...
Edda Leopold, Jörg Kindermann