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» Applying Support Vector Machines to Imbalanced Datasets
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ICML
2004
IEEE
14 years 11 months ago
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5
Text categorization algorithms usually represent documents as bags of words and consequently have to deal with huge numbers of features. Most previous studies found that the major...
Evgeniy Gabrilovich, Shaul Markovitch
ICNC
2005
Springer
14 years 3 months ago
Novel Leaning Feed-Forward Controller for Accurate Robot Trajectory Tracking
This paper presents a novel learning feed-forward controller design approach for accurate robotics trajectory tracking. Based on the joint nonlinear dynamics characteristics, a mod...
D. Bi, G. L. Wang, Jun Zhang, Q. Xue
CIS
2005
Springer
14 years 3 months ago
MFCC and SVM Based Recognition of Chinese Vowels
Abstract. The recognition of vowels in Chinese speech is very important for Chinese speech recognition and understanding. However, it is rather difficult and there has been no effi...
Fuhai Li, Jinwen Ma, Dezhi Huang
ESANN
2008
13 years 11 months ago
Discrimination of regulatory DNA by SVM on the basis of over- and under-represented motifs
In this paper we apply three pattern recognition methods (support vector machine, cluster analysis and principal component analysis) to distinguish regulatory regions from coding a...
Rene te Boekhorst, Irina I. Abnizova, Lorenz Werni...
ESANN
2008
13 years 11 months ago
On related violating pairs for working set selection in SMO algorithms
Sequential Minimal Optimization (SMO) is currently the most popular algorithm to solve large quadratic programs for Support Vector Machine (SVM) training. For many variants of this...
Tobias Glasmachers