nFOIL: Integrating Naïve Bayes and FOIL

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An optimization approach to learning falling rule lists (2017, background): “[1, 12, 15]), and any of these can be used to produce antecedents for our algorithm.”
Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME (2018, methodology): “Support Vector ILP [11] uses ILP hypotheses as kernel in dual form of the SVM algorithm. kFOIL [8] learns an incremental kernel for SVM algorithm using a FOIL style specialization. nFOIL [7] integrates the Naive-Bayes algorithm with FOIL.”
A statistical approach to rule learning (2006, methodology): “In a recent paper, Landwehr et al. (2006) present kFOIL, a version of FOIL modified to use kernels and SVMs in the rule induction step.”
Probabilistic Inductive Logic Programming (2004, methodology): “This idea has been followed with NFOIL, see [31] for more details.”