Abstract
This chapter begins with a brief discussion of some problems associated with input data. Then different rule types are defined. Three representative rule induction methods: LEM1, LEM2, and AQ are presented. An idea of a classification system, where rule sets are utilized to classify new cases, is introduced. Methods to evaluate an error rate associated with classification of unseen cases using the rule set are described. Finally, some more advanced methods are listed.
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CITATION STYLE
APA
Grzymala-Busse, J. W. (2009). Rule Induction. In Data Mining and Knowledge Discovery Handbook (pp. 249–265). Springer US. https://doi.org/10.1007/978-0-387-09823-4_13
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