Summary
A method of empirical and supervised learning to directly acquire knowledge from examples in form of classification rules is here proposed: the method combines a data analysis technique for linearly classifying with a conceptual method for generating disjunctive cover for each class, taking advantage of the peculiarities of both the approaches. Initial empirical results are encouraging.
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Esposito, F. (1990). Automated Acquisition of Production Rules by Empirical Supervised Learning Methods. In: Schader, M., Gaul, W. (eds) Knowledge, Data and Computer-Assisted Decisions. NATO ASI Series, vol 61. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-84218-4_3
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DOI: https://doi.org/10.1007/978-3-642-84218-4_3
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