Much effort has been spent during recent years to develop techniques for rule extraction from opaque models, typically trained neural networks. A rule extraction technique could use different strategies for the extraction phase, either a local or a global strategy. The main contribution of this paper is the suggestion of a novel rule extraction method, called Cluster and See Through (CaST), based on the global strategy. CaST uses parts of the well-known RX algorithm, which is based on the local strategy, but in a slightly modified way. The novel method is evaluated against RX and is shown to get as good as or better results on all problems evaluated, with much more compact rules. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Löfström, T., Johansson, U., & Niklasson, L. (2004). Rule extraction by seeing through the model. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3316, 555–560. https://doi.org/10.1007/978-3-540-30499-9_85
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