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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

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Empirical Investigation of the Effect of Pruning Artificial Neural Networks With Respect to Increased Generalization Ability

Weman, Nicklas January 2010 (has links)
This final thesis covers the basics of artificial neural networks, with focus on supervised learning, pruning and the problem of achieving good generalization ability. An empirical investigation is conducted on twelve dierent problems originating from the Proben1 benchmark collection.The results indicate that pruning is more likely to improve generalization if the data is sensitive to overtting or if the networks are likely to be trapped in local minima.
Artifical Neural Networks
Pruning
Empirical Investigation
Proben1
Magnitude Based Pruning
Optimal Brain Damage
Optimal Brain Surgeon
Computer Engineering
Datorteknik

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