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ICASSP
2010
IEEE
13 years 8 months ago
Multi-class SVM optimization using MCE training with application to topic identification
This paper presents a minimum classification error (MCE) training approach for improving the accuracy of multi-class support vector machine (SVM) classifiers. We have applied th...
Timothy J. Hazen
CVPR
2006
IEEE
14 years 9 months ago
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
We consider visual category recognition in the framework of measuring similarities, or equivalently perceptual distances, to prototype examples of categories. This approach is qui...
Alexander C. Berg, Hao Zhang 0003, Jitendra Malik,...
BIBE
2007
IEEE
167views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Assessing the Performance of Macromolecular Sequence Classifiers
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
Cornelia Caragea, Jivko Sinapov, Vasant Honavar, D...
BMCBI
2006
110views more  BMCBI 2006»
13 years 7 months ago
Bias in error estimation when using cross-validation for model selection
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Sudhir Varma, Richard Simon
AUSAI
2008
Springer
13 years 9 months ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan