Abstract
We describe statistical and empirical rule quality formulas and present an empirical comparison of them on standard machine learning datasets. From the experimental results, a set of formula-behavior rules are generated which show relationships between a formula's performance and dataset characteristics. These formula-behavior rules are combined into formula-selection rules which can be used in a rule induction system to select a rule quality formula before rule induction.
Cite
CITATION STYLE
An, A., & Cercone, N. (1999). An empirical study on rule quality measures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1711, pp. 482–491). Springer Verlag. https://doi.org/10.1007/978-3-540-48061-7_59
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