Identifying the most informative variables to discriminate between fatal and non-fatal road accidents-Reference-Cited by-同舟云学术

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Identifying the most informative variables to discriminate between fatal and non-fatal road accidents

Published:2023-12 Issue: Volume:14 Page:101093
ISSN:2213-624X
Container-title:Case Studies on Transport Policy
language:en
Short-container-title:Case Studies on Transport Policy

Author:

Karla Rocha Miriam,José Anzanello Michel,Harumi Yamashita Gabrielli,Caleffi Felipe,Cybis Helena

Publisher

Elsevier BV

Subject

Urban Studies,Transportation,Geography, Planning and Development

Reference58 articles.

1. Classification with class imbalance problem: A review;Ali;International Journal of Advances in Soft Computing and Its Applications,2015

2. Interpreting Quantitative Data with IBM SPSS Statistics;Antonius,2012

3. Anzanello, M. J.; Fogliatto, F., 2011. Selecting the best clustering variables for grouping mass-customized products involving workers’ learning. International Journal of Production Economics, p. 268-276, 2011.

4. Data mining-based method for identifying discriminant attributes in sensory profiling;Anzanello;Food Qual. Prefer.,2011

5. Selecting relevant Fourier transform infrared spectroscopy wavenumbers for clustering authentic and counterfeit drug samples;Anzanello;Sci. Justice,2014

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