Package: RLT 6.1.1

RLT: Reinforcement Learning Trees

Random forest with a variety of additional features for regression, classification, and survival analysis. Features include parallel computing with OpenMP, reproducibility with random seeds, variance and confidence band estimations using U-statistics, embedded model for selecting splitting variables and constructing linear combination splits, permutation and distribution-based variable importance, observation and variable weights, and subject tracking across trees.

Authors:Ruoqing Zhu [aut, cre, cph], Sarah Formentini [aut], Haowen Zhou [ctb], Tianning Xu [ctb], Zhechao Huang [ctb]