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Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04)
Speeding Up the Decision Making of Support Vector Classifiers
Kokubunji, Tokyo, Japan
October 26-October 29
ISBN: 0-7695-2187-8
Jonathan Milgram, ?cole de Technologie Sup?rieure
Mohamed Cheriet, ?cole de Technologie Sup?rieure
Robert Sabourin, ?cole de Technologie Sup?rieure
In this paper, we propose a new approach for speeding up the decision making of Support Vector Classifiers (SVC) in the context of multi-class classification. A two-stage system embedded within a probabilistic framework is presented. In the first stage we pre-estimate the posterior probabilities with a model-based approach and we re-estimate only the highest probabilities with appropriate SVCs in the second stage. We have tested our system on the benchmark database MNIST and the results show that our dynamic classification process allows to speedup the full "pairwise coupling" SVCs by a factor of 7.7 while preserving the accuracy. In addition, although the "one against all" strategy estimate slightly betters probabilities, our modular architecture seems more adapted to large multi-class problems.
Citation:
Jonathan Milgram, Mohamed Cheriet, Robert Sabourin, "Speeding Up the Decision Making of Support Vector Classifiers," iwfhr, pp.57-62, Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04), 2004
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