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Conference Papers Year : 2004

Optimal Brain Surgeon Variants for Feature Selection

Mohammed Attik
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Laurent Bougrain
Frédéric Alexandre


This paper presents three pruning algorithms based on Optimal Brain Surgeon (OBS) and Unit-Optimal Brain Surgeon (Unit-OBS). The first variant performs a backward selection by successively removing single weights from the input variables to the hidden units in a fully connected multilayer perceptron (MLP) for variable selection. The second one removes a subset of non-significant weights in one step. The last one combines the two properties presented above. Simulation results obtained on the Monk's problem illustrate the specificities of each method described in this paper according to the preserved variables and the preserved weights.
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Dates and versions

inria-00099923 , version 1 (26-09-2006)


  • HAL Id : inria-00099923 , version 1


Mohammed Attik, Laurent Bougrain, Frédéric Alexandre. Optimal Brain Surgeon Variants for Feature Selection. International Joint Conference on Neural Networks - IJCNN'04, 2004, Budapest, Hungary, 4 p. ⟨inria-00099923⟩
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