Source: Learning and Nonlinear Models. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS GENÉTICOS, RECONHECIMENTO DE TEXTO
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COUTINHO, Felipe Provezano e REZENDE, Solange Oliveira e ROSSI, Rafael Geraldeli. GA-TCTN: a framework for hyper-parameter optimization and text classification using transductive semi-supervised learning through term networks. Learning and Nonlinear Models, v. 17, n. 2, p. 27-41, 2019Tradução . . Disponível em: https://doi.org/10.21528/lmln-vol17-no2-art3. Acesso em: 07 set. 2024.APA
Coutinho, F. P., Rezende, S. O., & Rossi, R. G. (2019). GA-TCTN: a framework for hyper-parameter optimization and text classification using transductive semi-supervised learning through term networks. Learning and Nonlinear Models, 17( 2), 27-41. doi:10.21528/lmln-vol17-no2-art3NLM
Coutinho FP, Rezende SO, Rossi RG. GA-TCTN: a framework for hyper-parameter optimization and text classification using transductive semi-supervised learning through term networks [Internet]. Learning and Nonlinear Models. 2019 ; 17( 2): 27-41.[citado 2024 set. 07 ] Available from: https://doi.org/10.21528/lmln-vol17-no2-art3Vancouver
Coutinho FP, Rezende SO, Rossi RG. GA-TCTN: a framework for hyper-parameter optimization and text classification using transductive semi-supervised learning through term networks [Internet]. Learning and Nonlinear Models. 2019 ; 17( 2): 27-41.[citado 2024 set. 07 ] Available from: https://doi.org/10.21528/lmln-vol17-no2-art3