A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning

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Big data preprocessing: methods and prospects (2016, background): “Thus, a wide range of alternatives are available in the literature as we can see in some published reviews on the topic [36, 41, 42].”
A review of microarray datasets and applied feature selection methods (2014, methodology): “Discretization After presenting the measures related to information theory, we will discuss the topic of discretization [44] related to feature selection.”
ExploreKit: Automatic Feature Generation and Selection (2016, unknown): “Discretization [4] is necessary in many popular classification algorithms (e.”
Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study (2015, methodology): “It will probably obtain a better performance if a discretization process is used for continuous attributes [85,86].”