2026-06-17T18:23:20Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/50022024-05-20T07:08:25Zcom_10259_3830com_10259_5086com_10259_2604col_10259_3832
Repositorio Institucional de la Universidad de Burgos
author
Briz i Godino, Ivan
author
Ahedo García, Virginia
author
Álvarez, Myrian
author
Pal, Nélida .
author
Turnes, Lucas .
author
Santos Martín, José Ignacio
author
Zurro, Débora
author
Caro Saiz, Jorge
author
Galán Ordax, José Manuel
2018-11-09T10:04:08Z
2018-11-09T10:04:08Z
2018-10
2054-5703
http://hdl.handle.net/10259/5002
10.1098/rsos.180906
The present work aims to quantitatively explore and understand the relationship between mobility types (nautical versus pedestrian), specific technological traits and shared technological knowledge in pedestrian hunter–gatherer and nautical hunter–fisher–gatherer societies from the southernmost portion of South America. To that end, advanced statistical learning techniques are used: state-of-the-art classification algorithms and variable importance analyses. Results show a strong relationship between technological knowledge, traits and mobility types. Occupations can be accurately classified into nautical and pedestrian due to the existence of a non-trivial pattern between mobility and a relatively small fraction of variables from some specific technological categories. Cases where the best-fitted classification algorithm fails to generalize are found significantly interesting. These instances can unveil lack of information, not enough entries in the training set, singular features or ambiguity, the latter case being a possible indicator of the interaction between nautical and pedestrian societies.
eng
Attribution 4.0 International
Hunter–gatherer
Statistical learning
Shared technology
Random forest
Mobility
Hunter–gatherer mobility and technological landscapes in southernmost South America: a statistical learning approach
info:eu-repo/semantics/article
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URL
https://riubu.ubu.es/bitstream/10259/5002/1/Briz-rsos_2018.pdf
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https://riubu.ubu.es/bitstream/10259/5002/6/Briz-rsos_2018.pdf.txt
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Briz-rsos_2018.pdf.txt