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Ecological RationalityIntelligence in the World$
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Peter M. Todd and Gerd Gigerenzer

Print publication date: 2012

Print ISBN-13: 9780195315448

Published to Oxford Scholarship Online: May 2012

DOI: 10.1093/acprof:oso/9780195315448.001.0001

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Naïve, Fast, and Frugal Trees for Classification

Naïve, Fast, and Frugal Trees for Classification

Chapter:
14 Naïve, Fast, and Frugal Trees for Classification
Source:
Ecological Rationality
Author(s):

Laura F. Martignon

Konstantinos V. Katsikopoulos

Jan K. Woike

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195315448.003.0106

Naïve, fast, and frugal trees model simple classification strategies that ignore cue dependencies and process cues sequentially, one at a time. At every level of such a tree a classification is made for one of the considered cue values. This chapter demonstrates that naïve, fast, and frugal trees operate as lexicographic classifiers. On 30 data sets, the performance of such trees is compared with that of two commonly used classification methods: classification and regression trees (CART) and logistic regression. The naïve, fast, and frugal trees are surprisingly robust and their predictive accuracy is comparable to that of savvier competitors, especially when the training set is small. Given that such trees require less time and information and fewer calculations than more computationally complex methods, they represent an attractive option when classifications need to be made quickly and with limited resources.

Keywords:   classification, decision tree, lexicographic classifier, splitting profile, classification and regression tree, logistic regression

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