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Optimal Brain Surgeon Variants for Feature Selection

Mohammed Attik 1 Laurent Bougrain 1 Frédéric Alexandre 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : 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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https://hal.inria.fr/inria-00099923
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Submitted on : Tuesday, September 26, 2006 - 10:09:46 AM
Last modification on : Monday, April 19, 2021 - 5:30:05 PM
Long-term archiving on: : Wednesday, March 29, 2017 - 1:19:39 PM

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  • HAL Id : inria-00099923, version 1

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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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