Abstract
We are developing the GRG knowledge discovery system for learning decision rules from relational databases. The GRG system generalizes data, reduces the number of attributes, and generates decision rules. A subsystem of this software learns decision rules using familiar and novel rule induction techniques and uses these rules to make decisions. This paper provides an overview of GRG, describes those aspects of the system most relevant to creating and using decision rules, and compares it to other machine learning approaches.
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Shan, N., Hamilton, H.J., Cercone, N. (1997). Inducing and using decision rules in the GRG knowledge discovery system. In: van Someren, M., Widmer, G. (eds) Machine Learning: ECML-97. ECML 1997. Lecture Notes in Computer Science, vol 1224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62858-4_88
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DOI: https://doi.org/10.1007/3-540-62858-4_88
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