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  • This book provides new means for knowledge extraction with neural networks of the Back-Propagation type: to understand and interpret correctly the knowledge extracted by the network, detect significant, e.g. novel input patterns, identify their characteristic features and assess their future development. Two included case studies are devoted image classification and analysis of economical data provided by the World Bank.
  • This book provides new means for knowledge extraction with neural networks of the Back-Propagation type: to understand and interpret correctly the knowledge extracted by the network, detect significant, e.g. novel input patterns, identify their characteristic features and assess their future development. Two included case studies are devoted image classification and analysis of economical data provided by the World Bank. (en)
Title
  • Knowledge Extraction with Neural Networks: Significant Patterns and their Representation in Back-Propagation Networks
  • Knowledge Extraction with Neural Networks: Significant Patterns and their Representation in Back-Propagation Networks (en)
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  • Knowledge Extraction with Neural Networks: Significant Patterns and their Representation in Back-Propagation Networks
  • Knowledge Extraction with Neural Networks: Significant Patterns and their Representation in Back-Propagation Networks (en)
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  • RIV/00216208:11320/11:10103638!RIV12-GA0-11320___
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  • P(GAP103/10/0783), Z(MSM0021620838)
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  • 207572
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  • RIV/00216208:11320/11:10103638
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  • pruning; regularization; internal knowledge representation; back-propagation; neural networks; knowledge extraction (en)
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  • [870384CFF273]
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  • Saarbrucken, Germany
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  • Knowledge Extraction with Neural Networks: Significant Patterns and their Representation in Back-Propagation Networks
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  • Mrázová, Iveta
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  • LAP Lambert Academic Publishing
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  • 978-3-8443-2941-4
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  • 11320
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