AIC (Akaike's Information Criterion)
Ciência da Informação
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substantivo
Contexto: "Following Cai et al. (2014), we used a time-invariant bandwidth which was selected via minimising Akaike's information criterion (AIC) using a cross-sectional dataset comprising average summer daytime LST (land surface temperature), grass, shrub, tree, and precipitation for the three years the Urban Monitor data was available."
Fonte: Duncan, J. M. A., Boruff, B., Saunders, A., Sun, Q., Hurley, J., & Amati, M. (2019). Turning down the heat: An enhanced understanding of the relationship between urban vegetation and surface temperature at the city scale. Science of the Total Environment, 656, 118-128.
Fonte: Duncan, J. M. A., Boruff, B., Saunders, A., Sun, Q., Hurley, J., & Amati, M. (2019). Turning down the heat: An enhanced understanding of the relationship between urban vegetation and surface temperature at the city scale. Science of the Total Environment, 656, 118-128.
Termo equivalente: Critério de informação de Akaike
Definição: "Akaike’s Information Criterion (AIC) was firstly annunced by Akaike in 1971. In linear regression modelling, AIC is proposed as a model selection criterion since it estimates the quality of each model relative to other models."
Fonte: Darnius, O., & Manurung, A. (2019, October). Model selection in regression linear: a simulation based on akaike’s information criterion. In Journal of Physics: Conference Series (Vol. 1321, No. 2, p. 022085). IOP Publishing.
Fonte: Darnius, O., & Manurung, A. (2019, October). Model selection in regression linear: a simulation based on akaike’s information criterion. In Journal of Physics: Conference Series (Vol. 1321, No. 2, p. 022085). IOP Publishing.
Definição em português: "O Critério de Informação de Akaike (AIC) foi anunciado pela primeira vez por Akaike em 1971. Na modelagem de regressão linear, o AIC é proposto como critério de seleção de modelos, pois estima a qualidade de cada modelo em relação a outros modelos."