Entropy learning and relevance criteria for neural network pruning

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Entropy learning and relevance criteria for neural network pruning

In this paper, entropy is a term used in the learning phase of a neural network. As learning progresses, more hidden nodes get into saturation. The early creation of such hidden nodes may impair generalisation. Hence an entropy approach is proposed to dampen the early creation of such nodes by using...

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Bibliographic Details
Main Authors:	Geok, See Ng, Abdul Rahman, Abdul Wahab, Shi, Daming
Format:	Article
Language:	English
Published:	World Scientific Publishing Company 2003
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/38198/ http://irep.iium.edu.my/38198/1/Entropy_learning_and_relevance_criteria_for_neural_network_pruning.pdf

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