1. Standardizing interestingness measures for association rules.
- Author
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Shaikh, Mateen R., McNicholas, Paul D., Antonie, M. Luiza, and Murphy, Thomas Brendan
- Subjects
- *
SIMULATION methods & models , *DATA analysis , *ASSOCIATION rule mining , *DATA mining , *STANDARDIZATION - Abstract
Interestingness measures provide information about association rules. The value of an interestingness measure is often interpreted relative to the overall range of the interestingness measure. However, properties of individual association rules can further restrict what value an interestingness measure can achieve. These additional constraints are not typically taken into account in analysis, potentially misleading the investigator. Considering the value of an interestingness measure relative to this further constrained range provides greater insight than the original range alone and can even alter researchers' impressions of the data. Standardizing interestingness measures takes these additional restrictions into account, resulting in values that provide a relative measure of the attainable values. We explore the impacts of standardizing interestingness measures on real and simulated data. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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