Abstract
Wieland’s two-spiral problem is often used as a test for comparing the quality of different supervisedlearning algorithms and architectures. In this paper, we use this two-spiral problem to illustrate the advantages obtained from using all the additional knowledge about the problem domain in designing the neural net which solves a given problem. The characteristics of the knowledge-based net, with regard to complexity, number of elements, training speed and generalisation quality, make it appreciably better than alternative nets which make no use of this knowledge.
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Álvarez-Sánchez, J. Injecting Knowledge into the Solution of the Two-Spiral Problem. Neural Comput & Applic 8, 265–272 (1999). https://doi.org/10.1007/s005210050029
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DOI: https://doi.org/10.1007/s005210050029