Interestingness Measures for Association Patterns : A Perspective

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Learning customized and optimized lists of rules with mathematical programming (2018, background): “There is a large body of literature on interestingness measures for rules, such as lift, conviction, Laplace, and gain, and reviews of interestingness measures are given by Tan and Kumar [62], McGarry [44], Geng and Hamilton [24], and example methods are those of Simon et al [60], Fawcett [20].”
ORC: Ordered Rules for ClassificationA Discrete Optimization Approach to Associative Classification (2012, background): “There is a large body of literature on interestingness measures, such as lift, conviction, Laplace, and gain [review articles include those of Tan and Kumar, 2000, McGarry, 2005, Geng and Hamilton, 2006].”
Selecting the right objective measure for association analysis (2004, methodology): “This measure can be derived from the f-coefficient [30].”