A simple statistical model and association rule filtering for classification

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Learning customized and optimized lists of rules with mathematical programming (2018, methodology): “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, methodology): “Association rules were originally designed for data exploration, and later associative classification developed as a framework to use the rules for clas- sification, with algorithms such as CBA, CMAR, and CPAR [Liu et al., 1998, Li et al., 2001, Yin and Han, 2003, Simon et al., 2011].”
Mining Electronic Health Records: A Survey (2017, background): “; Cheng et al. 2016; Collins et al. 2011; Simon et al. 2011a; Mani et al. 2014; Matheny et al. 2010; Pakhomov et al. 2011; Fung et al. 2008; Wells et al. 2008; Vinzamuri et al. 2014; Li et al. 2015; van der Heijden et al. 2014; Jackson et al. 2011; Paxton et al. 2013; Zhao et al. 2011; Maroco et…”