An overview on subgroup discovery: foundations and applications

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Interpretable Decision Sets: A Joint Framework for Description and Prediction (2016, background): “Similarly, algorithms for problems such as subgroup discovery [24, 33, 40, 46], contrast set learning [3, 4, 30], and emerging pattern mining [17, 19] identify sets of rules to describe the relationships among variables and discover interesting patterns in the data.”
Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to? (2019, background): “Supervised descriptive rule discovery [50], and in particular subgroup discovery [51], [52], is also another interesting area of study.”
Machine learning for heterogeneous catalyst design and discovery (2018, methodology): “70 The SGD algorithm consists of three main parts: (1) the use of a description language for ﬁnding subgroups within a given pool of data; (2) the deﬁnition of utility functions that formalize the interestingness of subgroups; and (3) the use of a search algo-rithm to ﬁnd selectors that describe…”