Machine learning: a practical approach on the statistical learning theory (2018)
- Authors:
- USP affiliated authors: MELLO, RODRIGO FERNANDES DE - ICMC ; PONTI, MOACIR ANTONELLI - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-319-94989-5
- Assunto: APRENDIZADO COMPUTACIONAL
- Keywords: Statistical Learning Theory; Assessing Classification Algorithms; Support Vector Machines; Data Science
- Language: Inglês
- Imprenta:
- Descrição física: 380 p
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
MELLO, Rodrigo Fernandes de e PONTI, Moacir Antonelli. Machine learning: a practical approach on the statistical learning theory. . Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-94989-5. Acesso em: 28 maio 2025. , 2018 -
APA
Mello, R. F. de, & Ponti, M. A. (2018). Machine learning: a practical approach on the statistical learning theory. Cham: Springer. doi:10.1007/978-3-319-94989-5 -
NLM
Mello RF de, Ponti MA. Machine learning: a practical approach on the statistical learning theory [Internet]. 2018 ;[citado 2025 maio 28 ] Available from: https://doi.org/10.1007/978-3-319-94989-5 -
Vancouver
Mello RF de, Ponti MA. Machine learning: a practical approach on the statistical learning theory [Internet]. 2018 ;[citado 2025 maio 28 ] Available from: https://doi.org/10.1007/978-3-319-94989-5 - Color quantization in transfer learning and noisy scenarios: an empirical analysis using convolutional networks
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Informações sobre o DOI: 10.1007/978-3-319-94989-5 (Fonte: oaDOI API)
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