Standardizing interestingness measures for association rules

Statistical Analysis and Data Mining

Paul D. McNicholas¹  Mateen R. Shaikh²  M. Luiza Antonie³  Thomas Brendan Murphy⁴ 

[1] Department of Mathematics and Statistics McMaster University Hamilton Canada;Department of Mathematics and Statistics Thompson Rivers University Kamloops Canada;School of Computer Science University of Guelph Guelph Canada;School of Mathematics and Statistics University College Dublin Ireland

关键词: association rules;    frequency patterns;    interestingness measures;    standardizations;    text categorization;   

DOI  :  10.1002/sam.11394

学科分类：社会科学、人文和艺术（综合）

来源: John Wiley & Sons, Inc.

【 摘 要 】

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.

【 授权许可】

Unknown