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» Data selection for support vector machine classifiers
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ICIC
2009
Springer
15 years 4 months ago
Ensemble Classifiers Based on Kernel PCA for Cancer Data Classification
Now the classification of different tumor types is of great importance in cancer diagnosis and drug discovery. It is more desirable to create an optimal ensemble for data analysis ...
Jin Zhou, Yuqi Pan, Yuehui Chen, Yang Liu
ICIP
2001
IEEE
15 years 11 months ago
Combining support vector machines for accurate face detection
The paper proposes the application of majority voting on the output of several support vector machines in order to select the most suitable learning machine for frontal face detec...
Ioan Buciu, Constantine Kotropoulos, Ioannis Pitas
KES
2000
Springer
15 years 1 months ago
Multi-view face detection using support vector machines and eigenspace modelling
An approach to multi-view face detection based on head pose estimation is presented in this paper. Support Vector Regression is employed to solve the problem of pose estimation. T...
Yongmin Li, Shaogang Gong, Jamie Sherrah, Heather ...
BMCBI
2011
14 years 1 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
COLT
1999
Springer
15 years 2 months ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...