Abstract
The usual support/confidence framework to assess association rules has several drawbacks that lead to obtain many misleading rules, even in the order of 95% of the discovered rules in some of our experiments. In this paper we introduce a different framework, based on Shortliffe and Buchanan’s certainty factors and the new concept of very strong rules. The new framework has several good properties, and our experiments have shown that it can avoid the discovery of misleading rules.
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Berzal, F., Blanco, I., Sánchez, D., Vila, MA. (2001). A New Framework to Assess Association Rules. In: Hoffmann, F., Hand, D.J., Adams, N., Fisher, D., Guimaraes, G. (eds) Advances in Intelligent Data Analysis. IDA 2001. Lecture Notes in Computer Science, vol 2189. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44816-0_10
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DOI: https://doi.org/10.1007/3-540-44816-0_10
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