Is skipping the definition of primary and secondary models possible? Prediction of Escherichia coli O157 growth by machine learning.

Koyama, Kento; Kubo, Kyosuke; Hiura, Satoko; Koseki, Shige

Koyama, Kento; Kubo, Kyosuke; Hiura, Satoko; Koseki, Shige.

Afiliación

Koyama K; Graduate School of Agricultural Science, Hokkaido University, Kita-9, Nishi-9, Kita-ku, Sapporo 060-8589, Japan. Electronic address: kento.koyama@frontier.hokudai.ac.jp.
Kubo K; Graduate School of Agricultural Science, Hokkaido University, Kita-9, Nishi-9, Kita-ku, Sapporo 060-8589, Japan.
Hiura S; Graduate School of Agricultural Science, Hokkaido University, Kita-9, Nishi-9, Kita-ku, Sapporo 060-8589, Japan.
Koseki S; Graduate School of Agricultural Science, Hokkaido University, Kita-9, Nishi-9, Kita-ku, Sapporo 060-8589, Japan.

J Microbiol Methods ; 192: 106366, 2022 01.

Article en En | MEDLINE | ID: mdl-34774875

Asunto(s)

Carga Bacteriana/métodos; Escherichia coli O157/crecimiento & desarrollo; Microbiología de Alimentos/métodos; Máquina de Vectores de Soporte; Humanos; Crecimiento Demográfico

Palabras clave

Extremely randomized trees regression; Gaussian process regression; Predictive microbiology; Probability theory; Support vector regression

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Escherichia coli O157 / Carga Bacteriana / Máquina de Vectores de Soporte / Microbiología de Alimentos Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Microbiol Methods Año: 2022 Tipo del documento: Article

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