Hyperparameters
Mostrando 1-4 de 4 artigos, teses e dissertações.
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1. Machine learning para análises preditivas em saúde: exemplo de aplicação para predizer óbito em idosos de São Paulo, Brasil
Este estudo objetiva apresentar as etapas relacionadas à utilização de algoritmos de machine learning para análises preditivas em saúde. Para isso, foi realizada uma aplicação com base em dados de idosos residentes no Município de São Paulo, Brasil, participantes do estudo Saúde Bem-estar e Envelhecimento (SABE) (n = 2.808). A variável resposta fo
Cad. Saúde Pública. Publicado em: 29/07/2019
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2. Bayesian sequential procedure to estimate the viability of seeds Coffea arabica L. in tetrazolium test
ABSTRACT: Tetrazolium tests use conventional sampling techniques in which a sample has a fixed size. These tests may be improved by sequential sampling, which does not work with fixed-size samples. When data obtained from an experiment are analyzed sequentially the analysis can be terminated when a particular decision has been made, and thus, there is no nee
Sci. agric. (Piracicaba, Braz.). Publicado em: 2019-05
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3. Spatio-temporal hierarchical modelling of the coffee berry borer (Hypothenemus hampei Ferrari) dispersion in colombia. / Modelagem da distribuição espaço-temporal da broca do café (Hypothenemus hampaei Ferrari) em uma cultura da região central colombiana.
Study of agricultural pests distribution in space and time provides important information about the species dispersion mechanisms and its interaction with environmental factors. It also helps the development of sampling plans, the integrated pest management and planning of experiments. The aim of this work was to compare several hierarchical models in modell
Publicado em: 2002
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4. UMA ABORDAGEM SEQÜENCIAL ESPECTRAL NO ESTUDO DE SÉRIES TEMPORAIS NÃO ESTACIONÁRIAS / A SPECTRAL SEQUENTIAL APPROACH TO STUDY NON-STATIONARY TIME SERIE
Modelling and forecasting of times Series have been approached in many different ways. Lately, the most important approaches have been formulated in a space framework. The state space representation enables the state vector to be sequencially updated in time via the Kalman filter. In this dissertation, we present in a systematic way an approach to modelling
Publicado em: 1992