RCProb uses Dirichlet-smoothed class priors and Beta-smoothed condition likelihoods in a Naive Bayes formulation to extract rules from tree ensembles approximately 22 times faster than RuleCOSI+ while maintaining competitive accuracy and producing more compact rule sets on 33 benchmark datasets.
RuleCOSI+: Rule extraction for interpreting classi- fication tree ensembles.Information Fusion, 89:355–381, January 2023
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RCProb: Probabilistic Rule Extraction for Efficient Simplification of Tree Ensembles
RCProb uses Dirichlet-smoothed class priors and Beta-smoothed condition likelihoods in a Naive Bayes formulation to extract rules from tree ensembles approximately 22 times faster than RuleCOSI+ while maintaining competitive accuracy and producing more compact rule sets on 33 benchmark datasets.