Tractable classification with non-ignorable missing data using generative random forests (2022)
- Authors:
- USP affiliated authors: MAUÁ, DENIS DERATANI - IME ; LLERENA, JULISSA GIULIANA VILLANUEVA - IME
- Unidade: IME
- DOI: 10.5753/kdmile.2022.227969
- Subjects: MODELOS PARA PROCESSOS ESTOCÁSTICOS; APRENDIZADO COMPUTACIONAL
- Keywords: generative random forests; probabilistic circuits; non-ignorable missing data
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: SBC
- Publisher place: Porto Alegre
- Date published: 2022
- Source:
- Conference titles: Symposium on Knowledge Discovery, Mining and Learning - KDMiLe
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
VILLANUEVA LLERENA, Julissa Giuliana e MAUÁ, Denis Deratani. Tractable classification with non-ignorable missing data using generative random forests. 2022, Anais.. Porto Alegre: SBC, 2022. Disponível em: https://doi.org/10.5753/kdmile.2022.227969. Acesso em: 05 mar. 2026. -
APA
Villanueva Llerena, J. G., & Mauá, D. D. (2022). Tractable classification with non-ignorable missing data using generative random forests. In Anais. Porto Alegre: SBC. doi:10.5753/kdmile.2022.227969 -
NLM
Villanueva Llerena JG, Mauá DD. Tractable classification with non-ignorable missing data using generative random forests [Internet]. Anais. 2022 ;[citado 2026 mar. 05 ] Available from: https://doi.org/10.5753/kdmile.2022.227969 -
Vancouver
Villanueva Llerena JG, Mauá DD. Tractable classification with non-ignorable missing data using generative random forests [Internet]. Anais. 2022 ;[citado 2026 mar. 05 ] Available from: https://doi.org/10.5753/kdmile.2022.227969 - Cautious classification with data missing not at random using generative random forests
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Informações sobre o DOI: 10.5753/kdmile.2022.227969 (Fonte: oaDOI API)
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