unityForest: Improving Interaction Modelling and Interpretability in Random Forests

Implementation of the unity forest (UFO) framework (Hornung & Hapfelmeier, 2026, ). UFOs are a random forest variant designed to better take covariates with purely interaction-based effects into account, including interactions for which none of the involved covariates exhibits a marginal effect. While this framework tends to improve discrimination and predictive accuracy compared to standard random forests, it also facilitates the identification and interpretation of (marginal or interactive) effects: In addition to the UFO algorithm for tree construction, the package includes the unity variable importance measure (unity VIM), which quantifies covariate effects under the conditions in which they are strongest - either marginally or within subgroups defined by interactions - as well as covariate-representative tree roots (CRTRs) that provide interpretable visualizations of these conditions. Categorical and continuous outcomes are supported. This package is a fork of the R package 'ranger' (main author: Marvin N. Wright), which implements random forests using an efficient C++ backend.