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» Optimal feature selection for support vector machines
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TREC
2004
13 years 9 months ago
Feature Generation, Feature Selection, Classifiers, and Conceptual Drift for Biomedical Document Triage
We approached the problem of classifying papers for the TREC 2004 Genomics Track triage task as a four step process: feature generation, feature selection, classifier training, an...
Aaron M. Cohen, Ravi Teja Bhupatiraju, William R. ...
NIPS
1998
13 years 9 months ago
Dynamically Adapting Kernels in Support Vector Machines
The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
Nello Cristianini, Colin Campbell, John Shawe-Tayl...
ACSW
2004
13 years 9 months ago
Detecting Stress in Spoken English using Decision Trees and Support Vector Machines
This paper describes an approach to the detection of stress in spoken New Zealand English. After identifying the vowel segments of the speech signal, the approach extracts two dif...
Huayang Xie, Peter Andreae, Mengjie Zhang, Paul Wa...
PAKDD
2007
ACM
128views Data Mining» more  PAKDD 2007»
14 years 1 months ago
Selecting a Reduced Set for Building Sparse Support Vector Regression in the Primal
Recent work shows that Support vector machines (SVMs) can be solved efficiently in the primal. This paper follows this line of research and shows how to build sparse support vector...
Liefeng Bo, Ling Wang, Licheng Jiao
ICML
2010
IEEE
13 years 8 months ago
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
Mingkui Tan, Li Wang, Ivor W. Tsang