Optimization of Tree Ensembles

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From Tree Ensemble Models to Decisions

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Learning Optimal Classification Trees: Strong Max-Flow Formulations (2020, methodology): “For example, Nijssen and Fromont (2010) use itemset mining algorithms and Narodytska et al. (2018) use satisfiability (SAT) solvers. Verhaeghe et al. (2019) propose a more elaborate implementation combining several ideas from the literature, including branch-and-bound, itemset mining techniques and ”
Market Segmentation Trees (2019, background): “Mišić (2020) and Biggs et al. (2018) consider how to optimize the input features of tree ensembles in order to maximize the predicted value.”
Optimization Models for Machine Learning: A Survey (2019, background): “dels that make predictions based on aggregating the predictions of individual trees are also known as tree ensemble. A mixed integer optimization model for tree ensemble has been recently proposed in [168]. Decision trees can also be used in a more general range of applications as algorithms for pro”