Summary
Prototype based rules (P-rules) are an alternative to crisp and fuzzy rules, moreover they can be seen as a generalization of different forms of knowledge representation. In P-rules knowledge is represented as set of reference vectors, that may be derived from the SVM model.
The number of support vectors (SV) should be reduced to a minimal number that still preserves SVM generalization abilities. Several state-of-the-art methods that reduce the number of support vectors are compared with a new approach, taking into consideration possible interpretation of retained support vectors as the basis for P-rules.
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Blachnik, M., Duch, W. (2008). Prototype Rules from SVM. In: Diederich, J. (eds) Rule Extraction from Support Vector Machines. Studies in Computational Intelligence, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75390-2_7
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DOI: https://doi.org/10.1007/978-3-540-75390-2_7
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