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ICML
2006
IEEE
14 years 11 months ago
Locally adaptive classification piloted by uncertainty
Locally adaptive classifiers are usually superior to the use of a single global classifier. However, there are two major problems in designing locally adaptive classifiers. First,...
Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwo...
ICML
2006
IEEE
14 years 11 months ago
Efficient learning of Naive Bayes classifiers under class-conditional classification noise
We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
Christophe Nicolas Magnan, François Denis, ...
ICML
2003
IEEE
14 years 11 months ago
Kernel PLS-SVC for Linear and Nonlinear Classification
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
Roman Rosipal, Leonard J. Trejo, Bryan Matthews
ICIAP
2009
ACM
14 years 11 months ago
Multi-class Binary Symbol Classification with Circular Blurred Shape Models
Multi-class binary symbol classification requires the use of rich descriptors and robust classifiers. Shape representation is a difficult task because of several symbol distortions...
Sergio Escalera, Alicia Fornés, Oriol Pujol...
IDEAS
2007
IEEE
71views Database» more  IDEAS 2007»
14 years 4 months ago
Feature Space Enrichment by Incorporation of Implicit Features for Effective Classification
Feature Space Conversion for classifiers is the process by which the data that is to be fed into the classifier is transformed from one form to another. The motivation behind doin...
Abhishek Srivastava, Osmar R. Zaïane, Maria-L...