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» Training Data 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. ...
CANDC
2002
ACM
13 years 7 months ago
Drug Design by Machine Learning: Support Vector Machines for Pharmaceutical Data Analysis
We show that the support vector machine (SVM) classification algorithm, a recent development from the machine learning community, proves its potential for structure
Robert Burbidge, Matthew W. B. Trotter, Bernard F....
ICPR
2006
IEEE
14 years 8 months ago
Enhancing Training Set for Face Detection
We present a novel method to enhance training set for face detection with nonlinearly generated examples from the original data. The motivation is from Support Vector Machines (SV...
Ruiping Wang, Jie Chen, Shiguang Shan, Wen Gao
ICDM
2007
IEEE
109views Data Mining» more  ICDM 2007»
14 years 2 months ago
A Support Vector Approach to Censored Targets
Censored targets, such as the time to events in survival analysis, can generally be represented by intervals on the real line. In this paper, we propose a novel support vector tec...
Pannagadatta K. Shivaswamy, Wei Chu, Martin Jansch...
TSMC
2008
106views more  TSMC 2008»
13 years 7 months ago
Two Criteria for Model Selection in Multiclass Support Vector Machines
Abstract--Practical applications call for efficient model selection criteria for multiclass support vector machine (SVM) classification. To solve this problem, this paper develops ...
Lei Wang, Ping Xue, Kap Luk Chan