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ICML
2003
IEEE
14 years 8 months ago
Low Bias Bagged Support Vector Machines
Theoretical and experimental analyses of bagging indicate that it is primarily a variance reduction technique. This suggests that bagging should be applied to learning algorithms ...
Giorgio Valentini, Thomas G. Dietterich
ML
2007
ACM
130views Machine Learning» more  ML 2007»
13 years 7 months ago
A note on Platt's probabilistic outputs for support vector machines
Platt’s probabilistic outputs for Support Vector Machines (Platt, 2000) has been popular for applications that require posterior class probabilities. In this note, we propose an ...
Hsuan-Tien Lin, Chih-Jen Lin, Ruby C. Weng
ASC
2008
13 years 7 months ago
Dynamic classification for video stream using support vector machine
A dynamic classification using the support vector machine (SVM) technique is presented in this paper as a new `incremental' framework for multiple-classifying video stream da...
Mariette Awad, Yuichi Motai
KSEM
2009
Springer
14 years 2 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
ICML
2000
IEEE
14 years 8 months ago
Less is More: Active Learning with Support Vector Machines
We describe a simple active learning heuristic which greatly enhances the generalization behavior of support vector machines (SVMs) on several practical document classification ta...
Greg Schohn, David Cohn