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FFTrees: A toolbox to create, visualize, and evaluate fast-and-frugal decision trees

Phillips, Nathaniel D. and Neth, Hansjoerg and Woike, Jan K. and Gaissmaier, Wolfgang. (2017) FFTrees: A toolbox to create, visualize, and evaluate fast-and-frugal decision trees. Judgement and decision making, 12 (4). pp. 344-368.

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Official URL: http://edoc.unibas.ch/56351/

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Abstract

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 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.
Faculties and Departments:07 Faculty of Psychology
07 Faculty of Psychology > Departement Psychologie
07 Faculty of Psychology > Departement Psychologie > Forschungsbereich Sozial-, Wirtschafts- und Entscheidungspsychologie
07 Faculty of Psychology > Departement Psychologie > Forschungsbereich Sozial-, Wirtschafts- und Entscheidungspsychologie > Economic Psychology (Rieskamp)
UniBasel Contributors:Phillips, Nathaniel
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Society for Judgment and Decision Making
e-ISSN:1930-2975
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
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Last Modified:17 Jan 2018 11:30
Deposited On:17 Jan 2018 10:31

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