Knowledge Extraction from Artificial Neural Networks and Applications

@inproceedings{Ultsch1993KnowledgeEF,
  title={Knowledge Extraction from Artificial Neural Networks and Applications},
  author={Alfred Ultsch and Gabriela Guimar{\~a}es and Dieter Korus and Heng Li},
  year={1993}
}
Knowledge acquisition is a frequent bottleneck in artificial intelligence applications. Neural learning may offer a new perspective in this field. Using Self-Organising Neural Networks, as the Kohonen model, the inherent structures in high-dimensional input spaces are projected on a low dimensional space. The exploration of structures resp. classes is then possible applying the U-Matrix method for the visualisation of data. Since Neural Networks are not able to explain the obtained results, a… CONTINUE READING
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