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Clustering events into useful classifications is an important part of problem solving in engineering. This paper discusses the role of clustering in engineering and why numerical and conceptual clustering techniques are not always adequate. The <italic>knowledge based equation generator</italic> system was constructed to overcome one of these shortfalls.(More)
Empirical learning algorithms are hampered by their inability to use domain knowledge to guide the induction of new rules. This paper describes <italic>knowledge-based learning,</italic> an approach to learning that selects the examples and relevant attributes for an empirical algorithm. Knowledge-based learning can be used for developing rules for(More)
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