evtree: Evolutionary Learning of Globally Optimal Trees. Commonly used classification and regression tree methods like the CART algorithm are recursive partitioning methods that build the model in a forward stepwise search. Although this approach is known to be an efficient heuristic, the results of recursive tree methods are only locally optimal, as splits are chosen to maximize homogeneity at the next step only. An alternative way to search over the parameter space of trees is to use global optimization methods like evolutionary algorithms. The evtree package implements an evolutionary algorithm for learning globally optimal classification and regression trees in R. CPU and memory-intensive tasks are fully computed in C++ while the partykit package is leveraged to represent the resulting trees in R, providing unified infrastructure for summaries, visualizations, and predictions

References in zbMATH (referenced in 11 articles , 1 standard article )

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  1. Carrizosa, Emilio; Molero-Río, Cristina; Romero Morales, Dolores: Mathematical optimization in classification and regression trees (2021)
  2. Berk, Richard A.: Statistical learning from a regression perspective (2020)
  3. Erik Sverdrup; Ayush Kanodia; Zhengyuan Zhou; Susan Athey; Stefan Wager: policytree: Policy learning via doubly robust empirical welfare maximization over trees (2020) not zbMATH
  4. Höppner, Sebastiaan; Stripling, Eugen; Baesens, Bart; vanden Broucke, Seppe; Verdonck, Tim: Profit driven decision trees for churn prediction (2020)
  5. Asfha, Huruy Debessay; Kilinc, Betul Kan: Appraisal of performance of three tree-based classification methods (2018)
  6. Henckaerts, Roel; Antonio, Katrien; Clijsters, Maxime; Verbelen, Roel: A data driven binning strategy for the construction of insurance tariff classes (2018)
  7. Yukinobu Hamuro; Masakazu Nakamoto; Stephane Cheung; Edward Ip: mbonsai: Application Package for Sequence Classification by Tree Methodology (2018) not zbMATH
  8. Alvarez-Iglesias, Alberto; Hinde, John; Ferguson, John; Newell, John: An alternative pruning based approach to unbiased recursive partitioning (2017)
  9. Ott, Armin; Hapfelmeier, Alexander: Nonparametric subgroup identification by PRIM and CART: a simulation and application study (2017)
  10. Hothorn, Torsten: partykit: a modular toolkit for recursive partytioning in \textttR (2015)
  11. Thomas Grubinger; Achim Zeileis; Karl-Peter Pfeiffer: evtree: Evolutionary Learning of Globally Optimal Classification and Regression Trees in R (2014) not zbMATH