ORCID
- Woike, Jan K.: 0000-0002-6816-121X
Abstract
AbstractFast-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 FFTrees package. We then conduct a simulation across ten real-world datasets to test how well FFTs created by FFTrees can predict data. Simulation results show that FFTs created by FFTrees can predict data as well as popular classification algorithms such as regression and random forests, while remaining simple enough for anyone to understand and use.
DOI
10.1017/s1930297500006239
Publication Date
2017-07-01
Publication Title
Judgment and Decision Making
Volume
12
Issue
4
First Page
344
Last Page
368
ISSN
1930-2975
Organisational Unit
School of Psychology
Recommended Citation
Phillips, N., Neth, H., Woike, J., & Gaissmaier, W. (2017) 'FFTrees: A toolbox to create, visualize, and evaluate fast-and-frugal decision trees', Judgment and Decision Making, 12(4), pp. 344-368. Available at: https://doi.org/10.1017/s1930297500006239
