Cargando…
Uncertain imputation for time-series forecasting: Application to COVID-19 daily mortality prediction
The object of this study is to put forward uncertainty modeling associated with missing time series data imputation in a predictive context. We propose three imputation methods associated with uncertainty modeling. These methods are evaluated on a COVID-19 dataset out of which some values have been...
Autores principales: | Elimam, Rayane, Sutton-Charani, Nicolas, Perrey, Stéphane, Montmain, Jacky |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931261/ https://www.ncbi.nlm.nih.gov/pubmed/36812528 http://dx.doi.org/10.1371/journal.pdig.0000115 |
Ejemplares similares
-
The Use of Fitness-Fatigue Models for Sport Performance Modelling: Conceptual Issues and Contributions from Machine-Learning
por: Imbach, Frank, et al.
Publicado: (2022) -
Using shallow neural networks with functional connectivity from EEG signals for early diagnosis of Alzheimer's and frontotemporal dementia
por: Ajra, Zaineb, et al.
Publicado: (2023) -
A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method
por: Yang, Jun-He, et al.
Publicado: (2017) -
ImputeGAN: Generative Adversarial Network for Multivariate Time Series Imputation
por: Qin, Rui, et al.
Publicado: (2023) -
Time-series forecasting /
por: Chatfield, Christopher
Publicado: (2000)