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WINE
2005
Springer
268views Economy» more  WINE 2005»
15 years 11 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
ICPR
2002
IEEE
15 years 10 months ago
Tangent Distance Kernels for Support Vector Machines
When dealing with pattern recognition problems one encounters different types of a-priori knowledge. It is important to incorporate such knowledge into the classification method ...
Bernard Haasdonk, Daniel Keysers
CDC
2009
IEEE
117views Control Systems» more  CDC 2009»
15 years 10 months ago
Risk sensitive robust support vector machines
— We propose a new family of classification algorithms in the spirit of support vector machines, that builds in non-conservative protection to noise and controls overfitting. O...
Huan Xu, Constantine Caramanis, Shie Mannor, Sungh...
ICANN
2001
Springer
15 years 10 months ago
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller
IFIP7
2001
Springer
137views Optimization» more  IFIP7 2001»
15 years 10 months ago
Data Mining via Support Vector Machines
Support vector machines (SVMs) have played a key role in broad classes of problems arising in various fields. Much more recently, SVMs have become the tool of choice for problems...
Olvi L. Mangasarian