FFTrees: A toolbox to create, visualize, and evaluate fast-and-frugal decision trees - Nathaniel D. Phillips; Hansjörg Neth; Jan K. Woike; Wolfgang Gaissmaier (Judgment and Decision Making, 2017)
Fast-and-frugal trees (FFTs) are simple algorithms that facilitate efficient and accurate decisions based on limited information. But despite their successful use in many applied domains, there is no widely available toolbox that allows anyone to easily create, visualize, and evaluate FFTs. We fill this gap by introducing the R package FFTrees. In this paper, we explain how FFTs work, introduce a new class of algorithms called fan for constructing FFTs, and provide a tutorial for using the FFTreespackage. We then conduct a simulation across ten real-world datasets to test how well FFTs created by FFTreescan predictdata. Simulation results show that FFTs created by FFTreescan predict data as well as popular classification algorithms such as regression and random forests, while remaining simple enough for anyone to understand and use.
Keywords: 330