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Artigo de periodico
Red flag algorithms for Brazilian electronic invoices: outlier detection and price risk classification (2024)
Interian, Ruben ; Carpanese, Igor; Mello, Bruno; Ribeiro, Celso da Cruz Carneiro
Source: International Transactions in Operational Research. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, ALGORITMOS PARA PROCESSAMENTO, RECONHECIMENTO DE PADRÕES, NOTA FISCAL ELETRÔNICA, CORRUPÇÃO, LICITAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
INTERIAN, Ruben et al. Red flag algorithms for Brazilian electronic invoices: outlier detection and price risk classification. International Transactions in Operational Research, v. 31, n. 3, p. 1533-1553, 2024Tradução . . Disponível em: https://doi.org/10.1111/itor.13323. Acesso em: 10 nov. 2024.
APA
Interian, R., Carpanese, I., Mello, B., & Ribeiro, C. da C. C. (2024). Red flag algorithms for Brazilian electronic invoices: outlier detection and price risk classification. International Transactions in Operational Research, 31( 3), 1533-1553. doi:10.1111/itor.13323
NLM
Interian R, Carpanese I, Mello B, Ribeiro C da CC. Red flag algorithms for Brazilian electronic invoices: outlier detection and price risk classification [Internet]. International Transactions in Operational Research. 2024 ; 31( 3): 1533-1553.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1111/itor.13323
Vancouver
Interian R, Carpanese I, Mello B, Ribeiro C da CC. Red flag algorithms for Brazilian electronic invoices: outlier detection and price risk classification [Internet]. International Transactions in Operational Research. 2024 ; 31( 3): 1533-1553.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1111/itor.13323
Artigo de periodico
Challenges in benchmarking stream learning algorithms with real-world data (2020)
Souza, Vinícius Mourão Alves de ; Reis, Denis Moreira dos ; Maletzke, André Gustavo ; Batista, Gustavo Enrique de Almeida Prado Alves
Source: Data Mining and Knowledge Discovery. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, MINERAÇÃO DE DADOS, ALGORITMOS ÚTEIS E ESPECÍFICOS, BENCHMARKS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUZA, Vinícius Mourão Alves de et al. Challenges in benchmarking stream learning algorithms with real-world data. Data Mining and Knowledge Discovery, v. No 2020, n. 6, p. 1805-1858, 2020Tradução . . Disponível em: https://doi.org/10.1007/s10618-020-00698-5. Acesso em: 10 nov. 2024.
APA
Souza, V. M. A. de, Reis, D. M. dos, Maletzke, A. G., & Batista, G. E. de A. P. A. (2020). Challenges in benchmarking stream learning algorithms with real-world data. Data Mining and Knowledge Discovery, No 2020( 6), 1805-1858. doi:10.1007/s10618-020-00698-5
NLM
Souza VMA de, Reis DM dos, Maletzke AG, Batista GE de APA. Challenges in benchmarking stream learning algorithms with real-world data [Internet]. Data Mining and Knowledge Discovery. 2020 ; No 2020( 6): 1805-1858.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/s10618-020-00698-5
Vancouver
Souza VMA de, Reis DM dos, Maletzke AG, Batista GE de APA. Challenges in benchmarking stream learning algorithms with real-world data [Internet]. Data Mining and Knowledge Discovery. 2020 ; No 2020( 6): 1805-1858.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/s10618-020-00698-5
Artigo de periodico
Evaluation of statistical and machine learning models for time series prediction: identifying the state-of-the-art and the best conditions for the use of each model (2019)
Parmezan, Antonio Rafael Sabino; Souza, Vinícius M. A; Batista, Gustavo Enrique de Almeida Prado Alves
Source: Information Sciences. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, MINERAÇÃO DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PARMEZAN, Antonio Rafael Sabino e SOUZA, Vinícius M. A e BATISTA, Gustavo Enrique de Almeida Prado Alves. Evaluation of statistical and machine learning models for time series prediction: identifying the state-of-the-art and the best conditions for the use of each model. Information Sciences, v. 484, p. 302-337, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2019.01.076. Acesso em: 10 nov. 2024.
APA
Parmezan, A. R. S., Souza, V. M. A., & Batista, G. E. de A. P. A. (2019). Evaluation of statistical and machine learning models for time series prediction: identifying the state-of-the-art and the best conditions for the use of each model. Information Sciences, 484, 302-337. doi:10.1016/j.ins.2019.01.076
NLM
Parmezan ARS, Souza VMA, Batista GE de APA. Evaluation of statistical and machine learning models for time series prediction: identifying the state-of-the-art and the best conditions for the use of each model [Internet]. Information Sciences. 2019 ; 484 302-337.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1016/j.ins.2019.01.076
Vancouver
Parmezan ARS, Souza VMA, Batista GE de APA. Evaluation of statistical and machine learning models for time series prediction: identifying the state-of-the-art and the best conditions for the use of each model [Internet]. Information Sciences. 2019 ; 484 302-337.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1016/j.ins.2019.01.076
Artigo de periodico
Particle competition for complex network community detection (2008)
Quiles, Marcos Gonçalves; Liang, Zhao; Alonso, Ronaldo L; Romero, Roseli Aparecida Francelin
Source: Chaos. Unidade: ICMC
Subjects: REDES COMPLEXAS, MINERAÇÃO DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
QUILES, Marcos Gonçalves et al. Particle competition for complex network community detection. Chaos, v. 18, p. 033107-1-033107-10, 2008Tradução . . Disponível em: https://doi.org/10.1063/1.2956982. Acesso em: 10 nov. 2024.
APA
Quiles, M. G., Liang, Z., Alonso, R. L., & Romero, R. A. F. (2008). Particle competition for complex network community detection. Chaos, 18, 033107-1-033107-10. doi:10.1063/1.2956982
NLM
Quiles MG, Liang Z, Alonso RL, Romero RAF. Particle competition for complex network community detection [Internet]. Chaos. 2008 ; 18 033107-1-033107-10.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1063/1.2956982
Vancouver
Quiles MG, Liang Z, Alonso RL, Romero RAF. Particle competition for complex network community detection [Internet]. Chaos. 2008 ; 18 033107-1-033107-10.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1063/1.2956982

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