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Sparse Oblique Rule Boosting for Simpler Additive Rule Ensembles
Shahrzad Behzadimanesh, Pierre Le Bodic, Geoffrey I. Webb +1
Small additive ensembles of symbolic rules offer interpretable prediction models. Traditionally, these ensembles use rule conditions based on conjunctions of simple threshold propo…
Interpretable Representation Learning for Additive Rule Ensembles
Shahrzad Behzadimanesh, Pierre Le Bodic, Geoffrey I. Webb +1
Small additive ensembles of symbolic rules offer interpretable prediction models. Traditionally, these ensembles use rule conditions based on conjunctions of simple threshold propo…
Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles
Fan Yang, Pierre Le Bodic, Michael Kamp +1
Gradient boosting of prediction rules is an efficient approach to learn potentially interpretable yet accurate probabilistic models. However, actual interpretability requires to li…