Crime prediction through urban metrics and statistical learning (2018)
- Authors:
- Autor USP: RODRIGUES, FRANCISCO APARECIDO - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.physa.2018.03.084
- Subjects: REDES COMPLEXAS; CRIME; REGRESSÃO
- Keywords: Statistical learning; Complex systems; Random forest
- Language: Inglês
- Imprenta:
- Source:
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
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ABNT
ALVES, Luiz G. A. e RIBEIRO, Haroldo V. e RODRIGUES, Francisco Aparecido. Crime prediction through urban metrics and statistical learning. Physica A, v. 505, p. 435-443, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.physa.2018.03.084. Acesso em: 10 nov. 2024. -
APA
Alves, L. G. A., Ribeiro, H. V., & Rodrigues, F. A. (2018). Crime prediction through urban metrics and statistical learning. Physica A, 505, 435-443. doi:10.1016/j.physa.2018.03.084 -
NLM
Alves LGA, Ribeiro HV, Rodrigues FA. Crime prediction through urban metrics and statistical learning [Internet]. Physica A. 2018 ; 505 435-443.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1016/j.physa.2018.03.084 -
Vancouver
Alves LGA, Ribeiro HV, Rodrigues FA. Crime prediction through urban metrics and statistical learning [Internet]. Physica A. 2018 ; 505 435-443.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1016/j.physa.2018.03.084 - Unfolding the complexity of the global value chain: strength and entropy in the single-layer, multiplex, and multi-layer international trade networks
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Informações sobre o DOI: 10.1016/j.physa.2018.03.084 (Fonte: oaDOI API)
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