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» Optimal feature selection for support vector machines
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ICPR
2004
IEEE
14 years 8 months ago
Signal Discrimination Using a Support Vector Machine for Genetic Syndrome Diagnosis
In this study, a support vector machine (SVM) classifies real world data of cytogenetic signals measured from fluorescence in-situ hybridization (FISH) images in order to diagnose...
Amit David, Boaz Lerner
ISM
2005
IEEE
138views Multimedia» more  ISM 2005»
14 years 1 months ago
Investigation of Combining SVM and Decision Tree for Emotion Classification
This paper discusses the use of a combination of support vector machine and decision tree learning for recognizing four emotions in speech, which are Neutral, Angry, Lombard, and ...
Thao Nguyen, Mingkun Li, Iris Bass, Ishwar K. Seth...
CDC
2009
IEEE
117views Control Systems» more  CDC 2009»
14 years 14 days 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
14 years 7 days 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
DMIN
2009
132views Data Mining» more  DMIN 2009»
13 years 5 months ago
Understanding Support Vector Machine Classifications via a Recommender System-Like Approach
Support vector machines are a valuable tool for making classifications, but their black-box nature means that they lack the natural explanatory value that many other classifiers po...
David Barbella, Sami Benzaid, Janara M. Christense...