C4.5: Programs for Machine Learning by J. Ross Quinlan. Morgan Kaufmann Publishers, Inc., 1993

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Explaining Explanations: An Overview of Interpretability of Machine Learning (2018, methodology): “Similarly, The FERNN [37] algorithm uses the C4.5 algorithm [24] and tries to identify the meaningful hidden neurons and inputs to a particular network.”
Predicting Diabetes Mellitus With Machine Learning Techniques (2018, background): “In J48, the nodes are decided by information gain.”
Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning (2018, methodology): “Similarly, The FERNN [37] algorithm uses the C4.5 algorithm [24] and tries to identify the meaningful hidden neurons and inputs to a particular network.”
A Survey on ensemble learning under the era of deep learning (2021, methodology): “…(Rosenblatt 1958) TLA7 KNN K nearest neighbor (Altman 1992) TLA8 LR Logistic regression (Cox 1959) TLA9 C4.5 An improved iterative Dichotomiser 3 (Salzberg 1994) TLA10 AB AdaBoost (Freund and Schapire 1996) TLA11 CoKNN KNN based on cosine distance (Hu et al. 2016) TLA12 CuKNN KNN based on cubic…”
A novel feature-selection approach based on the cuttlefish optimization algorithm for intrusion detection systems (2015, methodology): “They used the genetic algorithm (GA) as a generator to produce an optimal subset of features, and then the produced featureswereused as an inputforthe DT thatwasconstructedusing the C4.5 algorithm.”